Key Terms
- Credits - Augment's billing unit for measuring usage. Each action (chat, agent turn, code review) consumes credits based on the model used, context size, and response length. For example, a small task with 10 tool calls costs roughly 300 credits; a complex task with 60 tool calls costs roughly 4,300 credits. Source: Augmentcode – Credit Based Pricing
- Context Engine - Augment's proprietary codebase indexing and retrieval system that provides real-time context to models. It indexes at repo scale and stays current with live changes. Source: Augmentcode – Context Engine
- Intent - Augment's agent orchestration workspace for spec-driven development. A coordinator breaks work into discrete tasks before execution. Currently macOS only. Source: Augmentcode – Intent
- Cosmos - Augment's operating system for agentic software development, launched in public preview on May 4, 2026. It runs specialized agents (called Experts) across the SDLC with shared memory, self-improving loops, and integrations with tools like Slack, GitHub, PagerDuty. Available to Max plan users. Source: Augmentcode – Cosmos Now In Public Preview
- Prism - A model routing system launched May 2, 2026 that routes each user turn to whichever underlying model best fits the work. Two variants: Prism (Claude + Gemini) routes between Opus 4.7, Sonnet 4.6, and Gemini Flash 3.0; Prism (GPT + Kimi) routes between GPT 5.5, GPT 5.4, and Kimi K2.6. Designed to cost 20-30% less than frontier model costs. Source: Augmentcode – Augment Prism Model Routing To Reduce Cost And Maintain Quality
- Expert - A specialized Cosmos agent with its own prompt, integrations, environment, secrets, event triggers, subscriptions, and worker experts. Examples: Incident Investigator, PR Author, Deep Code Review, Pair Reviewer. Source: Augmentcode – Cosmos Now In Public Preview
- Auggie CLI - Augment's command-line agent interface. Supports model switching mid-conversation via the
/modelcommand. Source: Augmentcode – Cli - Code Review - Augment's AI-powered PR review tool for GitHub pull requests, available on all paid plans. Enterprise tier adds advanced analytics, user allowlists, MCP configuration, multi-org support, and unlimited seats. Source: Augmentcode – Enterprise Features
- MCP (Model Context Protocol) - an open protocol for connecting AI agents to external tools and data sources. Augment supports MCP servers for integrations like Jira, Linear, and Notion. Source: Augmentcode – Context Engine Mcp
Latest Changes
Changes since the 2026-04 report.
- Feature added: Prism model routing launched (May 2). Two variants route between frontier and budget models per turn, targeting 20-30% cost reduction. Available in all interfaces (VS Code, JetBrains, CLI, web). Source: Augmentcode – Augment Prism Model Routing To Reduce Cost And Maintain Quality
- Feature added: Cosmos launched in public preview (May 4). Agent operating system with shared memory, Experts, and SDLC automation. Limited to Max plan ($200/dev/mo). Source: Augmentcode – Cosmos Now In Public Preview
- Feature added: Cosmos Sandboxes billing at 300 credits/hour, prorated in 5-minute increments. Source: Augmentcode – Credit Based Pricing
- Feature added: Prism (Claude + Gemini) routes between Opus 4.7, Sonnet 4.6, Gemini Flash 3.0 (new model entry). Source: Augmentcode – Credit Based Pricing
- Benchmark published: Auggie vs Claude Code head-to-head on Opus 4.7 (May 15). Auggie achieves 67.4% vs 66.3% pass rate on Terminal Bench 2.0 at 33% lower cost. On SWE-Bench Pro: 61.8% vs 59.9% at 23% lower cost. Source: Augmentcode – Auggie Beats Claude Code On Cost And Quality
- Research published: Survey of 219 engineering leaders (May 12). 48% of code now AI-generated, 55% concerned about losing codebase understanding, only 19 of 219 orgs have updated role definitions. Source: Augmentcode – Ai Native Survey 2026
- Case study published: Code review bottleneck solved with Cosmos (May 6). Code output up 3x since January while median merge time decreased. Bugs per output unit dropped from 0.097 peak to 0.006. Source: Augmentcode – Solving Code Review With Cosmos
- Case study published: Incident management with Cosmos (May 26). 81% reduction in human on-call investigation effort. Median time-to-first-RCA fell from 30.1 to 6.2 minutes. Source: Augmentcode – Scaling Incident Management For An Ai Native Organization Using Cosmos
- Community change: r/AugmentCodeAI subreddit moved to restricted mode (May 19). Only approved users can post. Source: Old – Our Subreddit Is Now In Restricted Mode
Plans
| Plan | Price (monthly) | Included credits | Auto top-up | Users | Credit pooling | Key inclusions |
|---|---|---|---|---|---|---|
| Indie | $20/mo | 40,000 | $15/24k credits | 1 | N/A (single user) | Context Engine, coding agent, chat, MCP, code review, Cosmos, SOC 2 Type II |
| Standard | $60/mo per dev | 130,000 | $15/24k credits | Up to 20 | Yes (team level) | Everything in Indie + Slack integration, usage analytics |
| Max | $200/mo per dev | 450,000 | $15/24k credits | Up to 20 | Yes (team level) | Everything in Standard + email-based support, Cosmos public preview access |
| Enterprise | Custom | Custom | Custom | Unlimited | Yes | SSO (OIDC), SCIM, CMEK, ISO 42001, SIEM integration, data residency, granular access controls, audit trails, dedicated support, volume-based annual discounts, custom VM sizes, multi-region VMs, unlimited concurrent sessions |
All paid plans include: no AI training on customer data, code review (PR summaries and inline comments, auto and manual mode, PR guidelines, MCP support), Cosmos (public preview for Max+), Prism model routing.
Cosmos Sandboxes: 300 credits/hour, prorated in 5-minute increments.
Credit top-ups not part of the base plan expire 12 months after purchase.
Source: Augmentcode – Pricing
Terms explained:
- CMEK (Customer-Managed Encryption Keys) - enterprise customers control their own encryption keys rather than relying on the provider's default key management. Available only on Enterprise plan.
- ISO 42001 - an international standard for AI management systems, covering risk management and governance of AI systems. Source: Augmentcode – Pricing
- SIEM (Security Information and Event Management) - integration with enterprise security monitoring tools like Splunk or Datadog to forward audit logs. Available only on Enterprise plan.
API Pricing
Augment Code does not offer a standalone API. It is a closed-platform coding agent accessed via IDE extensions (VS Code, JetBrains), the Auggie CLI, the Intent workspace, Cosmos web/cloud agents, Slack integration, and GitHub Code Review. There is no public token-based API pricing.
Instead, usage is billed through the credit system. Credit costs per model (based on a "standard medium-complexity task"):
| Model | Credits per task | Relative cost vs Sonnet 4.6 |
|---|---|---|
| Claude Haiku 4.5 | 88 | 30% |
| Kimi K2.6 | 147 | 50% |
| GPT-5.4 | 210 | 72% |
| GPT-5.1 | 219 | 75% |
| Gemini 3.1 Pro | 268 | 92% |
| Claude Sonnet 4.5 | 293 | 100% (baseline) |
| Claude Sonnet 4.6 | 293 | 100% (baseline) |
| GPT-5.2 | 390 | 133% |
| GPT-5.5 | 420 | 143% |
| Claude Opus 4.5 | 488 | 167% |
| Claude Opus 4.6 | 488 | 167% |
| Claude Opus 4.7 | 488 | 167% |
| Prism (Claude + Gemini) | Variable (routed) | Target: 20-30% less than Opus 4.7 |
| Prism (GPT + Kimi) | Variable (routed) | Target: 20-30% less than GPT 5.5 |
Prism routes between:
- Prism (Claude + Gemini): Opus 4.7, Sonnet 4.6, Gemini Flash 3.0
- Prism (GPT + Kimi): GPT 5.5, GPT 5.4, Kimi K2.6
Cosmos Sandboxes: 300 credits/hour, prorated in 5-minute increments.
Background activities (Context Compression, System) consume a "small fraction" of total credits. Specific numbers are undisclosed.
Source: Augmentcode – Credit Based Pricing
Model Performance / Benchmarks
Augment's Internal Multi-Turn Coding Benchmark (from Prism blog post, May 2)
Built from historical PRs on a large Go repo, converted into synthetic multi-message developer conversations. LLM judge scores diffs on correctness, completeness, code reuse, best practices, and unsolicited documentation (aggregate score in [-1, 1]).
| Model | Avg overall score (80% CI) | Cost per task |
|---|---|---|
| Prism (GPT + Kimi) | +0.30 +/- 0.14 | $5.25 |
| GPT 5.5 | +0.21 +/- 0.05 | $7.31 |
| Prism (Claude + Gemini) | +0.11 +/- 0.08 | $4.91 |
| Opus 4.7 | +0.08 +/- 0.10 | $6.81 |
| Sonnet 4.6 | -0.11 +/- 0.05 | $3.67 |
| Kimi K2.6 | -0.23 +/- 0.09 | $3.32 |
| Opus 4.6 | -0.37 +/- 0.19 | $5.16 |
Source: Augmentcode – Augment Prism Model Routing To Reduce Cost And Maintain Quality
Terminal Bench 2.0 (from Prism blog post, May 2)
| Model | Pass Rate | Cost per task |
|---|---|---|
| Prism (GPT + Kimi) | 75.7% | $0.68 |
| GPT 5.5 | 76.0% | $0.82 |
| Gemini 3.1 | 67.6% | $0.64 |
| GPT 5.4 | 66.5% | $0.49 |
| Opus 4.7 | 64.0% | $0.85 |
| Prism (Claude + Gemini) | 64.0% | $0.89 |
Source: Augmentcode – Augment Prism Model Routing To Reduce Cost And Maintain Quality
SWE-Bench Pro (from Prism blog post, May 2)
731 instances.
| Model | Pass Rate | Cost per instance |
|---|---|---|
| Opus 4.7 | 61.8% | $1.98 |
| Prism (Claude + Gemini) | 59.5% | $1.85 |
| GPT 5.5 | 53.6% | $2.15 |
| Prism (GPT + Kimi) | 52.9% | $1.88 |
Source: Augmentcode – Augment Prism Model Routing To Reduce Cost And Maintain Quality
Auggie CLI vs Claude Code on Opus 4.7 (from benchmark blog post, May 15)
Terminal Bench 2.0:
| Metric | Auggie CLI | Claude Code | Delta |
|---|---|---|---|
| Pass rate | 67.4% | 66.3% | +1.1% |
| Total cost | $463.04 | $694.50 | -33% |
| Total tokens | 367.6M | 543.1M | -32% |
| Output tokens | 7.2M | 11.4M | -37% |
| Cache read tokens | 342.0M | 506.5M | -32% |
| Cache write tokens | 18.0M | 25.2M | -29% |
SWE-Bench Pro:
| Metric | Auggie CLI | Claude Code | Delta |
|---|---|---|---|
| Pass rate | 61.8% | 59.9% | +1.9% |
| Total cost | $1,448.63 | $1,869.97 | -23% |
| Total tokens | 1.65B | 2.35B | -30% |
Auggie CLI across multiple models vs Claude Code on Opus 4.7 baseline (Terminal Bench 2.0):
| Configuration | Pass Rate | Cost | vs Baseline |
|---|---|---|---|
| GPT 5.5 | 76.0% | $362 | +9.3% pass rate, -48% cost |
| Gemini 3.1 | 67.6% | $283 | +1.3% pass rate, -59% cost |
| Opus 4.7 | 67.4% | $463 | +1.1% pass rate, -33% cost |
| GPT 5.4 | 66.5% | $215 | +0.2% pass rate, -69% cost |
Internal private repo evaluation (Opus 4.7):
| Metric | Auggie CLI | Claude Code |
|---|---|---|
| Tasks passed | 61/84 | 62/84 |
| Cost per passing task | $3.90 | $6.49 |
| Total spend | $238 | $402 |
Source: Augmentcode – Auggie Beats Claude Code On Cost And Quality
Cosmos Code Review Metrics (from code review blog post, May 6)
| Metric | Before Cosmos | After Cosmos |
|---|---|---|
| Code output (weekly) | ~500 (Nov) | ~1,850 (Apr) |
| Median PR merge time | ~700 min | ~250-350 min |
| Bugs per output unit (peak) | 0.097 (mid-Jan) | 0.006 (Apr 6) |
| Weekly revert rate target | 1.5% | Within +/- 0.5% of target |
Source: Augmentcode – Solving Code Review With Cosmos
Cosmos Incident Management Metrics (from incident blog post, May 26)
| Metric | Before Cosmos | After Cosmos |
|---|---|---|
| Incidents handled manually | 99.6% | 18.7% |
| Median time to first RCA | 30.1 min | 6.2 min |
| Median time to resolution (MTTR) | 29.5 min | 19.9 min |
| Merged PRs/week for on-call engineers | baseline | +44% |
Source: Augmentcode – Scaling Incident Management For An Ai Native Organization Using Cosmos
Latest News
Augment Prism: model routing to reduce cost and maintain quality (May 2, 2026)
Prism is a new option in the model picker that routes each user turn to whichever underlying model best fits the work. Two configurations: Prism (Claude + Gemini) targeting Opus 4.7 quality, and Prism (GPT + Kimi) targeting GPT 5.5 quality. On Augment's internal multi-turn benchmark, both Prism variants match or exceed their target model's quality at 20-30% lower cost per task. On Terminal Bench 2.0, Prism (GPT + Kimi) achieves 75.7% pass rate (vs GPT 5.5 at 76.0%) at $0.68/task (vs $0.82). On SWE-Bench Pro, Prism (Claude + Gemini) achieves 59.5% (vs Opus 4.7 at 61.8%) at $1.85/instance (vs $1.98).
The planner model adds ~2.6s median latency (p90 4.0s, p99 5.4s) on the ~4% of turns where it fires. The planner accounts for 0.03% of total spend. Prism is cache-aware: it only switches models when the expected win exceeds the cache eviction cost (~10x hit from evicting prompt cache).
For a team sending 10,000 user requests/month, Augment estimates ~$20,000 in monthly savings.
Limitations acknowledged: no way to surface the routed-to model, no way to constrain the routing pool, planner latency, no cost vs quality knob yet.
Source: Augmentcode – Augment Prism Model Routing To Reduce Cost And Maintain Quality
Cosmos public preview launched (May 4, 2026)
Augment Cosmos is described as "the operating system for agentic software development." It provides a platform for building, deploying, and managing specialized agents (Experts) that run across the SDLC. Key components: Agent Runtime, Context Engine, Event Bus, Organizational Knowledge Layer, Expert Registry, Knowledge Base, Human-in-the-Loop, Learning Flywheel. Agents can run on laptops, dev VMs, or Augment's cloud (customer cloud coming soon).
Cosmos is available in public preview for Max plan users ($200/dev/mo). The company acknowledges "rough edges" and says they prefer to learn in public.
Three core beliefs driving Cosmos: (1) individual agent adoption without organizational systems creates fragmentation, (2) the future is fully agentic software factories, (3) the platform must be model-agnostic to avoid provider lock-in.
Source: Augmentcode – Cosmos Now In Public Preview
How Cosmos solved the code review bottleneck (May 6, 2026)
Augment internally had 1,400 open PRs at peak with a 20-hour median time-to-first-comment. The solution was a team of Cosmos Experts: PR Risk Analyzer (auto-approves low-risk changes, initially 10% of PRs), Pair Reviewer (guides humans through structured review instead of line-by-line reading), Deep Code Review (line-by-line correctness analysis focused on bugs), PR Author (executes the PR lifecycle automatically), and Memory Manager (learns from every PR). Results: code output up 3x since January, median merge time decreased, bugs per output unit dropped from 0.097 to 0.006, weekly revert rate healthy around 1.5%.
Source: Augmentcode – Solving Code Review With Cosmos
AI-native engineering survey: 219 engineering leaders (May 12, 2026)
Key findings: 48% of code is now AI-generated. 55% concerned or very concerned about losing shared understanding of the codebase. 63% say engineers are raising fears about skill relevance. At largest teams (201-1,000 engineers), that number rises to 89%. The #1 hiring priority is now evaluating AI-generated code; traditional coding has dropped to #5. Only 19 of 219 orgs have formally changed role definitions. Leaders describe feeling "excited, anxious, invigorated" simultaneously.
Full report: Augmentcode – State Of Ai Native Engineering 2026
Source: Augmentcode – Ai Native Survey 2026
Auggie CLI beats Claude Code on cost and quality (May 15, 2026)
Head-to-head benchmark on Opus 4.7 using Terminal Bench 2.0 and SWE-Bench Pro. On Terminal Bench 2.0: Auggie 67.4% vs Claude Code 66.3% pass rate, $463 vs $695 total cost (33% reduction), 368M vs 543M total tokens (32% reduction). On SWE-Bench Pro: Auggie 61.8% vs Claude Code 59.9% pass rate, $1,449 vs $1,870 total cost (23% reduction). On private customer repos: Auggie passed 61 tasks vs Claude Code's 62, but at $3.90 vs $6.49 per passing task (40% reduction).
Token efficiency is attributed to the Context Engine providing sharper retrieval, resulting in fewer wasted exploration turns. GPT 5.5 on Auggie achieves the best quality (76.0% on Terminal Bench 2.0) at $362 (48% less than Claude Code on Opus 4.7 at $695). GPT 5.4 on Auggie achieves 66.5% at $215 (69% less).
Combined with Prism, Augment claims up to 50% total savings.
Source: Augmentcode – Auggie Beats Claude Code On Cost And Quality
Incident management with Cosmos (May 26, 2026)
Augment deployed an Incident Investigator Expert on Cosmos that runs triage and root cause analysis on every PagerDuty alert inside Slack. Results across five on-call channels over one month: agents now handle 81.3% of incidents (up from 0.4% before), median time-to-first-RCA fell from 30.1 to 6.2 minutes, median time to resolution fell from 29.5 to 19.9 minutes. On-call engineers saw a 44% increase in merged PRs/week. The investigator uses Agent Skills for logs and metrics analysis, and shared memory across experts.
Source: Augmentcode – Scaling Incident Management For An Ai Native Organization Using Cosmos
Changelog highlights (May 2026)
- Cosmos 26-05-25 (May 26): Custom environments no longer require Node.js, only bash and git needed.
- Cosmos 26-05-18 (May 18): Service account attribution for automated workflows, scoped webhook subscriptions, cloud agent hosted artifacts, file attachments in web conversations, org-scope shared files writable by all users. Bug fixes for daemon pool routing, session recovery from deleted snapshots, event delivery reliability.
- VSCode 0.859.7 (May 14): MCP Tool Search with settings toggle, conversation forking (editing earlier message branches into new thread), KaTeX math rendering, settings deep links. Bug fixes for checkpoints, MCP OAuth, chat recovery.
- IntelliJ 0.466.6 (May 14): Same features as VSCode release (MCP Tool Search, conversation forking, KaTeX, settings deep links). Fixed user/workspace guidelines not being included in chat requests.
- Auggie CLI 0.25.1 (May 3): Transcript persistence setting, non-interactive login via
--no-tuiflag. Fixed TUI flickering and stale agent state. - Prism launch (May 2): Prism model routing available in VS Code, JetBrains, CLI, and web.
Source: Augmentcode – Changelog
Community Signals
Reddit (r/AugmentCodeAI, May 2026)
Subreddit moved to restricted mode. On approximately May 19, the subreddit was set to restricted mode with the announcement "Our subreddit is now in restricted mode." Only approved users may post. This is a significant transparency signal. The post received 0 upvotes and 15 comments, but the comments are not accessible without login. This follows a pattern from April where the top post was a user switching to Claude Code (43 upvotes). Restricting posting may be an attempt to control negative sentiment.
Source: Old – Our Subreddit Is Now In Restricted Mode
"Full of bugs... I quit!! Good luck" (14 upvotes, 4 comments, 27 days ago). The top post this month by a user identified as "Either_Project9456" expressing frustration with bugs and leaving the platform. This is a stronger version of the April churn signal.
Source: Old – Top
"Any auto-complete alternatives for JetBrains/phpStorm?" (11 upvotes, 7 comments, 24 days ago). Users still seeking auto-complete alternatives, continuing the April complaint about code completion removal. The feature gap is persisting across months.
Source: Old – Top
"Oh boy oh boy! I'm tired..." (10 upvotes, 16 comments, 28 days ago). Another frustration post from the same user who posted the "Full of bugs" thread, suggesting persistent reliability issues affecting individual users.
Source: Old – Top
"How long is this going to remain broken with no response from the devs?" (6 upvotes, 18 comments, 27 days ago). A user posting a screenshot of a broken feature with frustration about lack of developer response. 18 comments suggests the issue resonated.
Source: Old – Top
Prism announcement (9 upvotes, 10 comments, 26 days ago). Official Augment Team post about Prism. 10 comments is moderate engagement for an official announcement.
Source: Old – Introducing Augment Prism Model Routing To Reduce
Cosmos public preview announcement (0 upvotes, 6 comments, 26 days ago). Low engagement for what Augment positions as their biggest launch.
Source: Old – We Dont Need More Agents We Need A Better System
"Did anyone tried Augment Cosmos?" (5 upvotes, 19 comments, 18 days ago). A genuine question from an early professional user about Cosmos experience. 19 comments is the highest comment count for a non-frustration post, suggesting genuine interest.
Source: Old – Did Anyone Tried Augment Cosmos
"Kimi 2.6 on Augment: New Models, Same Old Flakiness?" (4 upvotes, 17 comments, 23 days ago). A user reporting reliability issues persisting even with the new Kimi model. Title suggests a pattern of model additions not fixing underlying platform reliability.
Source: Old – Kimi 26 On Augment New Models Same Old Flakiness
Intent bugs continue. Multiple bug reports: "Intent refuses to start agents" (2 upvotes), "TypeError on non-string status prop, crashes error boundary" (0 upvotes, 5 comments), "Biggest Intent Painpoint - starting on non-default branch" (0 upvotes). Intent reliability remains an issue.
Source: Old – Top
HackerNews
No significant HackerNews discussions about Augment Code in May 2026. No HN submissions were found for Prism, Cosmos, or the Auggie vs Claude Code benchmark. The most recent relevant HN post about Augment was from December 2025 (12 points, 4 comments). Augment continues to have weak organic HN traction.
Source: Hn – Search
Enterprise Readiness
| Feature | Available? | Details |
|---|---|---|
| SSO (SAML) | No | SSO listed as OIDC only on Enterprise plan. Source: Augmentcode – Pricing |
| SSO (OIDC) | Yes | OIDC SSO on Enterprise plan. Source: Augmentcode – Pricing |
| SCIM | Yes | Enterprise plan. Source: Augmentcode – Pricing |
| Audit logs | Yes | Audit trails on Enterprise plan. Source: Augmentcode – Pricing |
| IP indemnity | No | Not mentioned on pricing or product pages. |
| Data residency | Yes | Enterprise plan. Source: Augmentcode – Pricing |
| HIPAA | No | Not mentioned on pricing or product pages. |
| Air-gapped / on-prem | No | Not available. Augment is a cloud-based platform. |
| SLA | Partial | Referenced ("same core uptime and response targets") but actual uptime percentage not on pricing page. Linked to separate legal page. Source: Augmentcode – Sla And Support Policy |
| Admin controls (RBAC) | Yes | Granular access controls, SIEM integration, CMEK on Enterprise plan. Source: Augmentcode – Pricing |
Cosmos-specific enterprise features (May 2026 additions):
- Service account attribution for automated workflows (Cosmos 26-05-18)
- Scoped webhook subscriptions (Cosmos 26-05-18)
- Org-scope shared files writable by all authenticated users (Cosmos 26-05-18)
Transparency Gaps
| Metric | Status | Details |
|---|---|---|
| Exact credit-to-token mapping | Undisclosed | Credits are an abstract unit. The conversion to actual token consumption per model is not published, making it impossible to compare Augment's credit pricing to raw API token pricing. |
| Rate limits (requests/min, requests/hour) | Undisclosed | No rate limit documentation found in pricing or docs. Users report hangs and flakiness (see Kimi 2.6 flakiness thread) but it is unclear whether these are rate limits, capacity issues, or bugs. |
| Context window per model | Undisclosed | Not specified in pricing or model docs. Different models have different context windows, but Augment does not document what context size each model receives. |
| Background activity credit consumption | Undisclosed ("small fraction") | Context Compression and System activities consume credits but specific percentages or ranges are not quantified. |
| Code Review credit cost | Undisclosed | Credits can be used for Code Review, but the per-PR credit cost is not itemized separately from agent/chat usage. |
| Prompt Enhancer credit cost | Undisclosed | Listed as a separate activity type in usage analytics but the per-use credit cost is not published. |
| "Standard medium-complexity task" definition | Vague | The credit-per-task table is based on a "standard medium-complexity task" but the task definition, prompt, and context size are not published. Actual credit consumption "varies based on task complexity, context size, and response length." |
| Enterprise pricing | Fully opaque | Listed as "Custom" with no starting price, per-seat range, or credit cost range. Requires sales contact. |
| SLA uptime target | Undisclosed on pricing page | The SLA is referenced ("same core uptime and response targets") but the actual uptime percentage and response time targets are not on the pricing page. Linked to a separate legal page. |
| Intent platform support timeline | Undisclosed | Intent is macOS-only. No public ETA for Windows or Linux support despite community demand. |
| Team size limits on Standard/Max | Up to 20 users | Standard and Max plans cap at 20 users but this is not prominently labeled as a limit. Teams of 21+ must go to Enterprise. |
| Auto top-up trigger threshold | Undisclosed | Auto top-up is available at $15/24k credits, but the trigger (when credits run out vs. when they reach a threshold) is not documented. |
| Prism underlying model per turn | Not surfaced | Prism hides the underlying model choice by design. Augment acknowledges this and plans to add a way to surface it for power users, but it is not yet available. |
| Prism planner latency | Disclosed in blog | 2.6s median (p90 4.0s, p99 5.4s) on the ~4% of turns where the planner fires. Not surfaced in the product UI. Source: Augmentcode – Augment Prism Model Routing To Reduce Cost And Maintain Quality |
| Cosmos availability by plan | Partially disclosed | Cosmos public preview is limited to Max plan ($200/dev/mo). Pricing or availability for Standard and Enterprise plans is not stated. |
| r/AugmentCodeAI restricted mode rationale | Undisclosed | The subreddit moved to restricted mode with no explanation of criteria for approved posters or the reasoning. This reduces community transparency. |
| Gemini Flash 3.0 availability | Undisclosed | Gemini Flash 3.0 appears as a Prism routing target in the docs but is not listed as a standalone model option. Its availability and pricing are unclear. |