Key Terms
- Wafer-Scale Engine (WSE-3) -- Cerebras's custom AI processor, roughly 58x larger than a standard GPU die, built for ultra-fast inference by keeping model weights on-chip and avoiding external-memory loads. Source: Cerebras – Chip
- Dedicated Endpoint -- A private, provisioned inference instance reserved for one organization, offering guaranteed throughput, custom model weights, and fine-tuning. Not available on the shared API; the 30+ model catalog lives here. Source: Inference-Docs – Overview
- Cerebras Code -- A flat-rate subscription product giving access to top open-weight models for coding via API, usable with third-party IDEs and CLI tools (not a standalone IDE). Both tiers are sold out. Source: Cerebras – Pricing
- Prompt Caching -- Stores and reuses previously processed prompt tokens to cut latency and cost on repeated queries. Cerebras lists prompt caching as supported on Gemma 4 31B and other models, but does not publish a price discount for cached tokens. Source: Inference-Docs – Gemma 4 31B
- Multi-LoRA -- Multi-adapter support for Low-Rank Adaptation, allowing per-request LoRA adapter switching on a single base model. Launched in private preview in May 2026 for dedicated endpoints. Source: Cerebras – Introducing Multi Lora On Cerebras Inference
- Multimodal / image input -- A model that accepts image inputs (screenshots, documents, charts) in addition to text. Gemma 4 31B is the first model on the Cerebras public API to support this. Source: Inference-Docs – Gemma 4 31B
- Artificial Analysis Intelligence Index -- A third-party composite score across ten benchmarks used to compare model quality. Cerebras cites it for speed-vs-quality positioning against closed models. Source: Cerebras – Gemma 4 On Cerebras The Fastest Inference Is Now Multimodal
Latest Changes
Changes since the 2026-05 report.
- New public model (coding-adjacent): Gemma 4 31B launched in public preview on June 29, 2026, the first Google DeepMind model and the first multimodal (image+text) model on the Cerebras public API. Artificial Analysis measured it at 1,851 output tokens/sec, described as 35x a typical GPU endpoint and 18x faster than Claude Haiku 4.5 (comparable quality: AA Intelligence Index 29 vs Haiku 4.5 at 30). Pricing $0.99 input / $1.49 output per MTok. Source: Cerebras – Gemma 4 On Cerebras The Fastest Inference Is Now Multimodal
- First earnings as a public company: On June 23, 2026 Cerebras reported Q1 2026 revenue of $193.4 million (+92% YoY from $99.5M), net loss narrowed to $14M (from $23.9M / 46 cents per share a year earlier). Source: Cnbc – Cerebras Cbrs Q1 Earnings Report 2026
- Margin guidance (financial risk): Core gross margin was 46.5% in Q1 but guided to 36-38% in Q2 and 38-41% for full-year 2026, partly due to a plan to rent back equipment from a large customer. CEO Andrew Feldman called the reaction "misunderstood." Stock fell ~10% after-hours June 23 and was down ~20% over the two-day window (closed $226.72 on June 23, down 28% from the $350 opening print). Source: Cnbc – Cerebras Cbrs Stock Earnings
- Sovereign AI deal (India/UAE): A May 15 agreement (reported June 1) will deploy a 64-system Cerebras AI supercomputer in India, operated by G42's Core42 unit with data under Indian governance. This is the first country on G42's "Intelligence Grid" sovereign-AI network. Source: Restofworld – India Uae G42 Cerebras Ai Sovereignty
- Customer concentration disclosed: G42 and MBZUAI together accounted for 86% of Cerebras' 2025 revenue per the SEC filing, flagged by Rest of World in June. Source: Restofworld – India Uae G42 Cerebras Ai Sovereignty
- Competitive comparison blog: On June 5 Cerebras published a head-to-head of Kimi K2.6 on Cerebras vs Google's newly launched Gemini 3.5 Flash. Cerebras claims 981 tok/s vs 181 tok/s (5.4x), end-to-end 5.6s vs 17.5s, and 452ms time-to-first-token vs 960ms for Flash, the first frontier model below the 500ms real-time-voice bar. Source: Cerebras – Which Is Faster Gemini 3 5 Flash Or Kimi K2 6 On Cerebras
- Cybersecurity partner blog: On June 15 Cerebras highlighted security use cases, naming Armis (AI for Security) and Operant AI (Security for AI) as partners using Cerebras inference. Source: Cerebras – Ai Inference Cybersecurity
- Developer-guidance blogs: "The Economics of AI Reasoning" (June 17) argued that reasoning adds ~6x tokens and 7-11x latency for ~10-20% quality gain, recommending disabling reasoning for simple agentic steps; "Never Loop Without Verifiers" (June 24) demonstrated Gemma 4 visual loops producing STEP files in ~1.2s at ~1,500 tok/s. Sources: Cerebras – The Economics Of Ai Reasoning , Cerebras – Never Loop Without Verifiers
- Plans still sold out (unchanged): Both Cerebras Code tiers (Pro $50/mo, Max $200/mo) remain listed as "sold out" as of June 30, 2026, with no reopening date announced. This is the second consecutive month of sold-out status. Source: Cerebras – Pricing
- Lock-up expiry: Per the IPO prospectus, roughly 28 million Class A shares held by directors, officers, and non-employee shareholders became tradeable on the second trading day after the June 23 earnings, under a staggered (not single-date) lock-up schedule. Source: Cnbc – Cerebras Cbrs Stock Earnings
Plans
Inference API Access
| Plan | Price | Rate Limits | Key Inclusions |
|---|---|---|---|
| Free | $0 | 5 RPM, 30K input tokens/min, 1M tokens/day (GPT OSS 120B / Gemma 4 / GLM 4.7) | Access to all three shared public models, community support via Discord |
| Developer | Self-serve, starting at $10 (pay-per-token) | 10x higher limits than Free (per-model: see API Pricing table); no daily token cap disclosed | Higher priority processing |
| Enterprise | Undisclosed (contact sales) | Highest limits (undisclosed), dedicated queue priority | Custom model weights, fine-tuning/training services, dedicated support team with response-time guarantees, Multi-LoRA, dedicated endpoints (30+ models) |
Terms explained:
- RPM -- Requests per minute, the standard API rate-limit unit.
- Self-serve starting at $10 -- Cerebras states the Developer tier starts at $10 but does not disclose what that buys in token credits or billing increments. Actual cost is usage-based per token. Source: Cerebras – Pricing
Cerebras Code (Subscription)
| Plan | Price | Token Allowance | Status |
|---|---|---|---|
| Pro | $50/month | Up to 24M tokens/day (~$48/day value) | Sold out |
| Max | $200/month | Up to 120M tokens/day (~$240/day value) | Sold out |
Both plans remain unavailable for purchase (second consecutive month). Source: Cerebras – Pricing
API Pricing
Per-token pricing on the shared public endpoint. All prices are per million tokens.
| Model | Model ID | Status | Input ($/MTok) | Output ($/MTok) | Speed (tok/s) | Context (paid) | Max Output (paid) | Modality |
|---|---|---|---|---|---|---|---|---|
| OpenAI GPT OSS 120B | gpt-oss-120b |
Production | $0.35 | $0.75 | ~3,000 | 131K | 40K | Text |
| Google Gemma 4 31B | gemma-4-31b |
Preview (NEW) | $0.99 | $1.49 | ~1,850 | 131K | 40K | Text + Image |
| Z.ai GLM 4.7 | zai-glm-4.7 |
Preview | $2.25 | $2.75 | ~1,000 | 131K | 40K | Text |
Sources: Inference-Docs – Overview , Inference-Docs – Gemma 4 31B , Inference-Docs – Openai Oss , Inference-Docs – Zai Glm 47
Rate Limits by Tier
| Model | Tier | Requests/min | Input Tokens/min | Daily Tokens |
|---|---|---|---|---|
| GPT OSS 120B | Free | 5 | 30K | 1M |
| GPT OSS 120B | Developer | 1,000 | 1M | N/A (undisclosed) |
| Gemma 4 31B | Free | 5 | 30K | 1M |
| Gemma 4 31B | Developer | 300 | 500K | N/A (undisclosed) |
| GLM 4.7 | Free | 5 | 30K | 1M |
| GLM 4.7 | Developer | 500 | 500K | N/A (undisclosed) |
Sources: Inference-Docs – Gemma 4 31B , Inference-Docs – Overview
Dedicated Endpoint Models (Enterprise Only)
The dedicated-endpoint catalog spans 30+ models across 10+ families. Key coding-relevant families:
| Model Family | Key Models |
|---|---|
| Alibaba Qwen | Qwen3-235B-A22B, Qwen3-Coder-480B-A35B, Qwen3-32B, Qwen3-30B-A3B |
| OpenAI OSS | GPT-OSS-120B, GPT-OSS-20B |
| Moonshot AI | Kimi-K2.6, Kimi-K2.5, Kimi-K2-Instruct, Kimi-K2-Thinking |
| Z.AI | GLM-5.1, GLM-5, GLM-4.7, GLM-4.7-Flash, GLM-4.6 |
| DeepSeek | DeepSeek-V3.2, DeepSeek-V3.1, DeepSeek-V3 |
| Meta | Llama-4-Maverick (402B), Llama-4-Scout (109B), Llama-3.3-70B |
| Mistral | Mistral-Large-3-675B, Devstral-Small-2-24B, Codestral-22B |
| MiniMax | MiniMax-M2.5, MiniMax-M2.1 |
| ByteDance | Seed-OSS-36B |
| ServiceNow | Apriel-1.6-15B-Thinker |
Dedicated-endpoint pricing is not publicly listed. Source: Inference-Docs – Overview
Model Performance / Benchmarks
Cerebras publishes speed (verified by Artificial Analysis) but does not publish its own coding-quality benchmarks for served models; quality numbers below come from the model creators.
| Model | Metric | Value | Source |
|---|---|---|---|
| Gemma 4 31B | Output speed (Artificial Analysis) | 1,851 tok/s (35x typical GPU, 18x Haiku 4.5) | Cerebras – Gemma 4 On Cerebras The Fastest Inference Is Now Multimodal |
| Gemma 4 31B | AA Intelligence Index (quality) | 29 (vs Haiku 4.5 at 30) | Cerebras – Gemma 4 On Cerebras The Fastest Inference Is Now Multimodal |
| Gemma 4 31B | Time-to-first-token (incl. reasoning) | 1.5 seconds | Cerebras – Gemma 4 On Cerebras The Fastest Inference Is Now Multimodal |
| Kimi K2.6 | Output speed on Cerebras | 981 tok/s | Cerebras – Which Is Faster Gemini 3 5 Flash Or Kimi K2 6 On Cerebras |
| Kimi K2.6 | Time-to-first-token (aiewf-eval voice benchmark) | 452ms (first frontier model under 500ms with CoT on) | Cerebras – Which Is Faster Gemini 3 5 Flash Or Kimi K2 6 On Cerebras |
| Kimi K2.6 | SWE-Bench Pro (model-level) | 58.6% (vs Gemini 3.5 Flash 55.1%) | Cerebras – Which Is Faster Gemini 3 5 Flash Or Kimi K2 6 On Cerebras |
| Gemini 3.5 Flash | Output speed (Artificial Analysis, reference) | 181 tok/s | Cerebras – Which Is Faster Gemini 3 5 Flash Or Kimi K2 6 On Cerebras |
| GPT OSS 120B | Output speed (Cerebras measurement) | ~3,000 tok/s | Inference-Docs – Openai Oss |
| GLM 4.7 | Output speed (Cerebras measurement) | ~1,000 tok/s | Inference-Docs – Zai Glm 47 |
Note: SWE-Bench Pro and AA Intelligence Index scores are model-level benchmarks published by model creators or Artificial Analysis. Cerebras contributes inference speed, not model capability. The blog comparison "Qwen-3.6-27B and Gemma-4-31B with reasoning, both beating last year's SOTA Sonnet-4" is a Cerebras-authored claim without a numeric benchmark citation. Source: Cerebras – The Economics Of Ai Reasoning
Latest News
Gemma 4 31B Launch, First Multimodal Model (June 29, 2026)
Gemma 4 31B launched in public preview as the first Google DeepMind model and the first multimodal (image + text) model on Cerebras. Artificial Analysis measured 1,851 tok/s, positioning it as 18x faster than Claude Haiku 4.5 at comparable quality (AA Intelligence Index 29 vs 30). Pricing is $0.99/$1.49 per MTok. Cerebras recommends it as the "reference medium-size model" and an open-weight Haiku/GPT-OSS/Llama alternative. Image inputs are base64 only (no URLs), max 5 images / 10MB per request, Chat Completions endpoint only. Source: Cerebras – Gemma 4 On Cerebras The Fastest Inference Is Now Multimodal
First Quarterly Earnings as a Public Company (June 23, 2026)
Q1 2026 revenue was $193.4 million, up 92% year-over-year from $99.5 million. Net loss narrowed to $14 million from $23.9 million a year earlier (loss per share 22 cents vs 46 cents). Core gross margin was 46.5% in Q1 but guided to 36-38% for Q2 and 38-41% for the full year, with core revenue guided to roughly $914 million (88% YoY growth) for Q2 and $855.5M-$865M (69% growth at midpoint) for the full year. The stock fell ~10% in extended trading and closed the next session at $226.72, down 28% from its $350 post-IPO opening print. Source: Cnbc – Cerebras Cbrs Q1 Earnings Report 2026
CEO Defends Margin Guidance (June 24, 2026)
CEO Andrew Feldman told CNBC the margin forecast was "misunderstood," stating Cerebras is beating the plan it laid out pre-IPO, and attributed part of the margin compression to a plan to rent back equipment from one of its largest clients. He also noted the staggered lock-up (about 28 million Class A shares becoming tradeable after earnings) and that Cerebras does not face the HBM or TSMC advanced-node supply pressure confronting Nvidia. Mizuho and Wedbush raised estimates following the call. Source: Cnbc – Cerebras Cbrs Stock Earnings
India/UAE Sovereign AI Supercomputer (reported June 1, 2026)
A May 15 agreement will deploy a 64-system Cerebras AI supercomputer in India, installed and operated by G42's Core42 unit with Cerebras providing technical support; all data remains under Indian governance. India is the first country on G42's "Intelligence Grid." Rest of World reported G42 and MBZUAI together accounted for 86% of Cerebras' 2025 revenue, and that G42 became Cerebras's largest customer in 2021. Source: Restofworld – India Uae G42 Cerebras Ai Sovereignty
Kimi K2.6 vs Gemini 3.5 Flash Comparison (June 5, 2026)
Ahead of the Gemini 3.5 Flash launch context, Cerebras published a head-to-head. On the Artificial Analysis 10K-input/500-output test, Kimi K2.6 on Cerebras completed in 5.6 seconds at 981 tok/s vs Gemini 3.5 Flash at 17.5 seconds and 181 tok/s. On the aiewf-eval voice benchmark Kimi K2.6 hit 452ms time-to-first-token vs Flash's 960ms. On SWE-Bench Pro, Kimi K2.6 scored 58.6% vs Gemini 3.5 Flash 55.1%. Source: Cerebras – Which Is Faster Gemini 3 5 Flash Or Kimi K2 6 On Cerebras
Economics of AI Reasoning (June 17, 2026)
A Cerebras-authored analysis argued reasoning produces ~6x more tokens and 7-11x longer completion times for a ~10-20% quality gain on coding/agentic benchmarks, and that 87.5%+ of tokens for a model like Qwen-3.6-27B are reasoning tokens. The recommendation is to treat reasoning as a cost/speed toggle and disable it for the ~50% of simple agentic steps. Source: Cerebras – The Economics Of Ai Reasoning
Never Loop Without Verifiers (June 24, 2026)
A practical post on building verified agent loops, demonstrating Gemma 4 producing a new STEP (CAD) file roughly every 1.2 seconds at ~1,500 tok/s, with the loop rewriting its own prompt across five iterations to clone a physical object from a photo. Source: Cerebras – Never Loop Without Verifiers
Cybersecurity Inference Edge (June 15, 2026)
A post positioning fast inference for security workflows, naming Armis (AI for Security: unified application-security context and remediation) and Operant AI (Security for AI: inline runtime defense for prompts, tool calls, and data flows) as Cerebras partners. Source: Cerebras – Ai Inference Cybersecurity
Community Signals
Gemma 4 launch thread: fast, but unclear who pays for a fast medium model
The HackerNews thread for the Gemma 4 launch reached 23 points and 8 comments. Commenters were impressed by the speed but questioned the value proposition of a fast, smaller, cloud-hosted model. Source: News – Item
- tmanchester: "Okay this is actually pretty cool. Gemma 4 is a nice little model and I've really enjoyed playing around with it. At 1800 tok/s turns are essentially instant, it's a bit of a trip." News – Item
- simianwords: "I just tried it on their website and it is extremely fast. I wonder what is the value prop of this? Where would I want 1. a smaller model 2. also non local, hosted on cloud. I can't think of any case." News – Item
- anthonypasq: "speed is always better. if you have ever used a coding agent with 1000 tps going back to 50 seems like walking through sludge. for simple question i hate waiting 2 minutes for opus to loop 50 times just to read some files and answer a question." News – Item
- simianwords (reply): "Of course I think speed is preferable but I don't see myself paying for a fast Gemma." News – Item
- johntash: "OCR is a decent use-case for smaller models. I've had good experience using gemma for OCR'ing handwritten stuff that tesseract doesn't do so well on." News – Item
Earnings reaction: minimal developer-community engagement
The CNBC story on Cerebras's post-earnings stock drop ("Cerebras CEO says margin forecast misunderstood as stock plummets after earnings") drew only 8 points and zero comments on HackerNews, consistent with the May IPO submission (3 points, 0 comments). The developer community remains focused on product availability, not Cerebras's financials. Source: News – Item
Sovereign AI deal drew more attention than the IPO or earnings
The India/UAE sovereignty story ("India, UAE partner on AI sovereignty to bypass Google, Microsoft") reached 36 points and 12 comments, the highest-engagement Cerebras-adjacent HN submission of June. The framing around bypassing US cloud dominance and the 86% customer-concentration figure drove the discussion. Source: News – Item
Cerebras cited as the speed benchmark in a local-inference "Ask HN"
In an Ask HN about fast coding models on Apple Silicon (M4 Max, 128GB), the author used Cerebras as the reference point: "Cerebras offers gpt-oss-120b at over 1000t/s, but it's so expensive and also isn't able to properly call tools most of the time." This echoes the recurring May theme that Cerebras's speed advantage is real but model quality/tool-calling reliability on open-weight models trails Claude. Source: News – Item
Sold-out Cerebras Code subscriptions remain an unaddressed frustration
No June Cerebras blog post, press release, or pricing-page update announced a reopening of the Pro ($50/mo) or Max ($200/mo) Cerebras Code tiers. The earlier August 2025 launch thread (449 points, 172 comments) remains the locus of ongoing frustration, and the topic carries forward unresolved into June. Source: News – Item
Enterprise Readiness
| Feature | Available? | Details |
|---|---|---|
| SSO (SAML/OIDC) | Undisclosed | Not mentioned in pricing, docs, or enterprise tier description. Contact sales. |
| SCIM | Undisclosed | Not mentioned in public documentation. |
| Audit logs | Undisclosed | Not mentioned. Dedicated-endpoint metrics are available in Prometheus format. Source: Inference-Docs – Metrics |
| IP indemnity | No | Cerebras is an inference provider, not a model creator; indemnity would depend on the underlying model. Not mentioned in Cerebras's own terms. |
| Data residency | Partial | Sovereign AI initiative supports on-premises deployment in specific countries (US, UAE, India); the June-reported India deal keeps data under Indian governance. Cloud inference data residency is otherwise undisclosed. Source: Restofworld – India Uae G42 Cerebras Ai Sovereignty |
| HIPAA | Undisclosed | Not mentioned in public documentation. |
| Air-gapped/on-prem | Yes | Cerebras CS-3 systems are sold as hardware for customer datacenters; the India/G42 deployment is a 64-system on-sovereign-soil example. Source: Cerebras – Ai Supercomputer |
| SLA | Undisclosed | Enterprise tier mentions "response time guarantees" for support, but inference SLA (uptime, latency) is not publicly documented. |
| Admin controls (RBAC) | Partial | Cloud Console supports Projects for organizing workloads and team access. Full RBAC details not publicly documented. Source: Inference-Docs – Projects |
Transparency Gaps
| Gap | Details | Severity |
|---|---|---|
| Cerebras Code plans still sold out (2 months) | Both Pro ($50/mo) and Max ($200/mo) remain sold out as of June 30 with no reopening timeline. This blocks the primary flat-rate access point for individual developers for the second consecutive month. | High |
| Customer concentration | G42 and MBZUAI accounted for 86% of 2025 revenue (per SEC filing). The margin-guidance drop is partly tied to renting equipment back from a large customer, but which customer and the contract terms are not disclosed. | High |
| Prompt caching pricing | Prompt caching is listed as a supported capability (including on Gemma 4 31B), but no price discount for cached input tokens is published. Competitors (Anthropic, Google) make this explicit. | High |
| Developer tier daily token cap | Rate-limit tables list "N/A" for daily tokens on Developer tier for all three public models. Either there is no cap or it is not disclosed. | Medium |
| Enterprise / dedicated-endpoint pricing | No pricing, rate limits, or SLA terms are public for the Enterprise tier or the 30+ dedicated-endpoint models. Buyers must engage sales. | High |
| Gross-margin mix detail | The 46.5% to 36-38% Q2 margin drop is attributed partly to an equipment rent-back from a large customer and "data center pass-through revenues," but the breakdown between inference-API margin and hardware/systems margin is not separated in public disclosures. | Medium |
| SSO/SCIM/audit logs/HIPAA | None of these enterprise-compliance controls are mentioned in pricing, docs, or the enterprise tier description. | High |
| Lock-up mechanics | ~28M Class A shares became tradeable under a staggered schedule after June 23 earnings, but the full staged-release calendar is not summarized on the investor page. | Low |
| Model quality benchmarks | Cerebras publishes speed benchmarks but no independent coding-quality benchmarks (SWE-Bench, LiveCodeBench) for the models it serves. Quality claims rely on model creators or Artificial Analysis. | Medium |
| Gemma 4 "preview" status | Gemma 4 31B is labeled preview ("may be discontinued on short notice") with no production commitment or GA date. GLM 4.7 carries the same preview caveat. | Medium |
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*Sources: All pricing and plan data from Cerebras – Pricing and Inference-Docs – Overview (accessed 2026-06-30). Financial data from CNBC Q1 earnings coverage (June 23-24, 2026). Sovereign-AI data from Rest of World (June 1, 2026). Blog data from Cerebras – Blog. Community signals from Hacker News.*