Cerebras

Key Terms

• Wafer-Scale Engine (WSE-3 / WSE-3 Turbo) -- Cerebras's custom AI processor that uses an entire silicon wafer as one chip, keeping model weights in on-wafer SRAM (44 GB, 21 PB/s aggregate bandwidth, ~900,000 cores) instead of off-chip HBM. CS-4 uses three overclocked WSE-3 Turbo processors. Sources: Cerebras – How Cerebras Serves Gpt 5 6 Sol At Up To 750 Tokens Per Second , Cerebras – Introducing Cerebras Cs 4
• Cerebras Code -- the former flat-rate subscription ($50/mo Pro, $200/mo Max) for coding with open-weight models. Sold out since roughly May 2026, described as unavailable in August, and as of September no longer listed on the pricing page at all. Source: Cerebras – Pricing
• Dual-bucket rate limits -- every organization gets an uncached tokens/min limit and a separate total tokens/min limit (default 3x uncached). Cached hits do not count against the uncached bucket, so a higher cache hit rate raises effective throughput without changing the limit. Source: Inference-Docs – Rate Limits
• Prompt caching (Cerebras) -- automatic prefix caching in 128-token blocks with a guaranteed 5-minute TTL (up to 1 hour). Cached tokens reduce latency but are billed at the standard input rate; there is no cache discount. Source: Inference-Docs – Prompt Caching
• Free Trial tier -- new accounts get a one-time $5 promotional credit after adding a payment method; it expires 30 days after activation and there is no permanently free tier. Source: Inference-Docs – Rate Limits
• GPT-5.6 Sol Ultrafast -- an OpenAI-previewed mode of GPT-5.6 Sol served on Cerebras WSE-3 at up to 750 output tok/s, using the same weights, precision, and reasoning settings as the standard endpoint. Not sold on the Cerebras pricing page; it is an OpenAI product. Source: Cerebras – How Cerebras Serves Gpt 5 6 Sol At Up To 750 Tokens Per Second
• Dedicated Inference -- private, provisioned endpoints for one organization with production SLAs, reserved capacity, custom weights, and fine-tuning; where the 30+ model catalog lives. Source: Inference-Docs – Overview
• Nexus / CS-4 -- Cerebras's fourth-generation system built on the Nexus modular rack platform (three Wafer-Scale Backpacks, pluggable power, RoCE v2 / Direct Wafer Link I/O), claimed up to 30x faster inference than GPU systems and up to 10x more throughput per watt than CS-3. Source: Cerebras – Introducing Cerebras Cs 4
• Neocloud -- a cloud provider that finances and operates specialized AI hardware and resells it as capacity, e.g. General Compute, which signed a multi-year Cerebras deal on Sep 29 backed by a $400M debt facility. Source: Cerebras – General Compute Selects Cerebras To Bring Ultra Fast Inference To Agentic Coding
• Disaggregated inference -- splitting inference so prefill (processing the prompt) runs on GPU/ASIC platforms (AMD Helios, AWS Trainium) while Cerebras does ultra-low-latency decode. Native in CS-4. Source: Cerebras – Introducing Cerebras Cs 4

Latest Changes

Changes since the 2026-08 report.

• New model: Qwen 3.8 27B (qwen-3.8-27b) went live on the shared API, Alibaba's 27B dense multimodal model for agentic coding, at $0.99/$1.49 per MTok and ~1,850 tok/s, with image inputs, reasoning defaulting to high, and tool calling; announced via docs around Sep 3 and confirmed by a 691-point HN thread. Sources: Inference-Docs – Qwen 3.8 27B , News – Item
• Model removed: Gemma 4 31B was pulled from the shared API the same day Qwen 3.8 launched; its docs page returns 404 and the pricing page now lists only two models, with users reporting no migration notice beyond a Discord heads-up a week earlier. Sources: Inference-Docs – Gemma 4 31B , News – Item
• Subscription delisted: Cerebras Code (Pro $50/mo, Max $200/mo) no longer appears anywhere on the pricing page, which now shows only Developer and Enterprise tiers; August described it as "subscriptions unavailable" for four months, and September removes it from the catalog entirely with no closure announcement. Source: Cerebras – Pricing
• Rate-limit redesign: limits moved to a dual-bucket model (uncached TPM vs total TPM); Qwen 3.8 Developer gets 300 RPM, 150K uncached TPM, 750K total TPM (temporarily raised from 450K), while GPT OSS 120B Developer keeps 1K RPM and 1M uncached/3M total TPM, and Developer tier has no hourly or daily caps. Source: Inference-Docs – Rate Limits
• Caching policy documented: prompt caching is automatic on all models in 128-token blocks (5-minute guaranteed TTL), but cached tokens bill at the full input rate; the docs now state this explicitly, ending ambiguity about the August "undisclosed" status while keeping the zero-discount policy. Source: Inference-Docs – Prompt Caching
• Free tier eliminated: the docs now state there is no permanently free tier; new accounts get a one-time $5 credit that expires after 30 days, replacing the recurring free allowances (1M tokens/day) described in the June report. Source: Inference-Docs – Rate Limits
• Hardware launch: CS-4 introduced Aug 18 with three WSE-3 Turbo processors, up to 30x faster inference than GPU systems, 1,000+ tok/s on 10T+ parameter models, 2-microsecond wafer-to-wafer latency, and first shipments beginning this quarter. Source: Cerebras – Introducing Cerebras Cs 4
• OpenAI expansion: GPT-5.6 Sol Ultrafast preview at up to 750 output tok/s on Cerebras (Aug 27), same weights and precision as standard Sol, with 5.6x faster task completion on quality-matched GDP-Val and 6.9x on Humanity's Last Exam. Source: Cerebras – How Cerebras Serves Gpt 5 6 Sol At Up To 750 Tokens Per Second
• New distribution channel: multi-year agreement with General Compute (announced Sep 29), a neocloud financing alternative chips, with agentic coding as the first use case; Cerebras inference available through General Compute from Q1 2027. Source: Cerebras – General Compute Selects Cerebras To Bring Ultra Fast Inference To Agentic Coding
• Roadmap: at Hot Chips (Aug 25) Cerebras detailed CS-5 (2027 target: up to 10,000 tok/s per user on open-source models, 5,000 tok/s on multi-trillion-parameter models, 3M tokens/sec per MW) and CS-6 with 3D-stacked DRAM at wafer scale. Source: Cerebras – Ultrafast Frontier Inference Cerebras Deep Dive At Hot Chips 2026

Plans

Cerebras Code (Subscription)

The pricing page no longer contains any subscription product: it lists exactly two tiers, Developer and Enterprise. This is the fifth consecutive month without purchasable flat-rate coding access, and the first month the product is not even listed. No reopening or official sunset announcement was found on the blog, pricing page, or press releases this cycle; community discussion in the Qwen launch thread treats the plan as gone ("The coding plan is gone now right?", News – Item). One user described the old acquisition mechanism: allocations were dropped via Discord and gone in under a minute (News – Item). Source: Cerebras – Pricing

Inference API Access

Terms explained:

• No permanent free tier -- the Free Trial is credit-bounded ($5, 30 days); once exhausted, API and Playground access pause until PayGo credits are purchased. Source: Inference-Docs – Rate Limits
• Temporary total-TPM boost -- Qwen 3.8's 750K total TPM is explicitly labeled "temporarily increased from the standard 450K (3x uncached) to 750K (5x uncached)" with no end date. Source: Inference-Docs – Rate Limits

Partner channels for the same inference: AWS Marketplace, OpenRouter, Hugging Face, and Vercel. Separately, GPT-5.6 Sol Ultrafast (750 tok/s) is sold by OpenAI, not on Cerebras's own pricing page. Source: Cerebras – Pricing

API Pricing

Per-token pricing on the shared public endpoint, verified live. All prices are per million tokens. Billing is token-based, not character-based.

Sources: Inference-Docs – Overview , Inference-Docs – Qwen 3.8 27B , Inference-Docs – Openai Oss , Cerebras – Pricing

Cache pricing: there is no cached-token discount. "Input tokens, whether served from the cache or processed fresh, are billed at the standard input token rate for the respective model." Cache TTL is guaranteed 5 minutes (up to 1 hour), blocks are 128 tokens, and caching is automatic for all customers and models. Source: Inference-Docs – Prompt Caching

Off-catalog: GPT-5.6 Sol Ultrafast at up to 750 tok/s is served for OpenAI's endpoint, with no Cerebras-side price published. The Aug 27 blog lists dedicated-endpoint families including Kimi K2.6, GLM 5.1, MiniMax M2.5, Qwen3 Coder 480B, Llama 4 Maverick, Mistral Large 3, and DeepSeek V3.2; dedicated pricing is not public. Sources: Cerebras – How Cerebras Serves Gpt 5 6 Sol At Up To 750 Tokens Per Second , Inference-Docs – Overview

Rate Limits by Tier (dual-bucket)

Source: Inference-Docs – Rate Limits

Model Performance / Benchmarks

Cerebras publishes throughput and latency numbers but no independent coding-quality benchmarks (SWE-Bench, Terminal-Bench, LiveCodeBench) for models it serves. Qwen 3.8 27B's coding capability claims come from Alibaba's model card, not Cerebras.

Note: CS-4 "30x" figures are Cerebras-sourced (Artificial Analysis plus internal benchmarking, August 2026); no third-party audit of the CS-4 claims exists yet, and the comparison does not disclose the GPU models, counts, power, or prices involved (community criticism: News – Item). A day earlier, The Register argued Cerebras and Nvidia market peak performance customers rarely see (News – Item).

Latest News

Qwen 3.8 27B Launch and Same-Day Gemma 4 Removal (September 3, 2026)

Qwen 3.8 27B, described in the docs as "Alibaba's 27B dense multimodal model for agentic coding, tool use, research, and long-running workflows," appeared on the shared API at $0.99/$1.49 per MTok and ~1,850 tok/s, with text and image inputs (base64 PNG/JPEG, up to 10 images/request on Developer), reasoning defaulting to high (disable with reasoning_effort: none), structured outputs, parallel tool calling, and prompt caching. The same day, Gemma 4 31B (launched June 29 as the first multimodal model) was removed; its docs page 404s. Users report only a soft Discord heads-up about a week earlier. The launch reached 691 points and 228 comments on HackerNews. Sources: Inference-Docs – Qwen 3.8 27B , Inference-Docs – Overview , News – Item

General Compute Neocloud Deal, Agentic Coding First (September 29, 2026)

General Compute, a neocloud for alternative chips backed by a $400M debt facility from Upper90, signed a multi-year agreement to deploy Cerebras inference at scale, with agentic coding as the first use case ("Agents make thousands of sequential calls, and latency compounds into wall-clock time," said GC CEO Finn Puklowski). Cerebras CTO Sean Lie framed it as putting Cerebras speed in front of developers on a platform they already use. Availability through General Compute starts Q1 2027; the deal is financed by lenders rather than hardware purchases, which Cerebras presents as a new go-to-market path for inference providers. Source: Cerebras – General Compute Selects Cerebras To Bring Ultra Fast Inference To Agentic Coding

AlphaSense Case Study with Numbers (September 30, 2026)

A joint engineering post detailed how AlphaSense's Generative Search uses Cerebras for fast, repeated model calls (routing, query generation, snippet evaluation): p90 time-to-first-token fell 88% from 19.5 seconds to 2.3 seconds with the same model served 8.5x faster, initial results arrive in 10-20 seconds (up to twice as fast as other providers), and evidence review volume tripled without added latency. Source: Cerebras – How Alphasense Uses Fast Inference To Make Agentic Research Interactive

CS-4 Launch, First Shipments This Quarter (August 18, 2026)

CS-4 is the fourth-generation system: three WSE-3 Turbo processors on the Nexus modular rack platform, with up to 30x faster inference than GPU systems, 1,000+ tok/s on models beyond 10 trillion parameters, wafer-to-wafer latency as low as 2 microseconds, up to 10x more throughput per watt than CS-3, native disaggregated inference (prefill on AMD Helios or AWS Trainium, decode on Cerebras), 50% fewer components, and RoCE v2 / Direct Wafer Link I/O. First shipments began in the launch quarter. The HN thread reached 464 points and 275 comments. Sources: Cerebras – Introducing Cerebras Cs 4 , News – Item

GPT-5.6 Sol Ultrafast at 750 tok/s (August 27, 2026)

OpenAI is previewing an Ultrafast mode of GPT-5.6 Sol running on Cerebras at up to 750 output tok/s, partitioned at layer boundaries across multiple CS-3 systems, with identical weights, precision, and reasoning settings to the standard endpoint (no distillation or quantization). On quality-matched GDP-Val tasks it finished 5.6x faster, and 6.9x faster on matched Humanity's Last Exam questions. This is a major-customer win, not a Cerebras-catalog product: pricing and availability sit with OpenAI. Source: Cerebras – How Cerebras Serves Gpt 5 6 Sol At Up To 750 Tokens Per Second

Hot Chips Deep Dive: CS-5 and CS-6 Roadmap (August 25, 2026)

Cerebras detailed CS-4 power delivery (AC/DC converters 0.5mm from the wafer, ~100x closer than GPU boards, up to 30 power modules per backpack) and previewed CS-5 (2027: up to 10,000 output tok/s per user on leading open-source models, 5,000 tok/s on multi-trillion-parameter models like Kimi and GPT-5.6 Sol, 3M tokens/sec per MW, support for 50T+ parameter models) and CS-6 (wafer-scale SRAM plus 3D-stacked DRAM). The post's forward-looking-statements section names OpenAI, G42, MBZUAI, and AWS as significant customers and references a Master Relationship Agreement with OpenAI. Source: Cerebras – Ultrafast Frontier Inference Cerebras Deep Dive At Hot Chips 2026

Agentic QA for the Cloud Console (September 8, 2026)

Cerebras described console-prompt-tests, an internal framework where tests are plain-English paragraphs run by an LLM agent driving a real browser through Playwright MCP, with self-healing of UI-drift failures, a PR coverage agent, risk-scored release gates, and a ~20-minute automated release doc. It is being extended to the API Gateway and API Server, a concrete example of Cerebras dogfooding agentic coding workflows on its own models. Source: Cerebras – We Taught An Ai Agent To Qa Our Cloud Console In Plain English

Other September Posts

The blog also published "Why Cyber Defense Needs Faster Inference" (Sep 24) and "The rise of slow personal assistants" (Sep 24), plus "Disaggregated Inference From The Ground Up" on Oct 1; none changed pricing, models, or limits. Source: Cerebras

Community Signals

Qwen 3.8 27B launch: 691 points, 228 comments, the highest-engagement Cerebras story of the month

The thread ("Qwen 3.8 27B available on Cerebras at 1500 tokens/s", News – Item) split between genuine excitement about speed and sharp criticism of Cerebras's developer-relations handling.

• On the same-day Gemma removal, puppymaster: "They just simply do not care about non enterprise customers. Today they announced qwen, guess what - it's also the same day they pulled Gemma off their shared tier. No migration notice and all developers are scrambling as we speak trying to migrate. They gave a soft head-ups on discord a week ago and when folks complained about zero-day migration they started saying 'you aren't supp[osed to use it in production]'" News – Item
• dshat: "I'm saddened that Gemma4 is replaced by Qwen 3.8 on PayGo plan. Gemma4 31B is not coding model but it is excellent at intent understanding and task execution used in agentic software." News – Item
• On cost without a cache discount, eli ran a commit-review session: "The Cerebras session cost me $1.60 and took a total of 5.1 mins. I did get a few brief 429 rate limit errors in there. The p50 speed was 890 tok/s and 0.64s TTFT. Using OpenRouter averages, that would've cost $0.29" News – Item and followed up: "The session had a 91.4% cache hit rate. They just give zero discount." News – Item
• On rate limits, gpugreg: "There is a limit of 450,000 tokens per minute. I hit this limit in about 90 seconds and burned through $1.10 while doing so. This is because cached tokens count towards the token limit. For comparison, I ran the same task with DeepSeek-V4-Flash, which finished in 172 seconds and cost $0.024" News – Item
• On the coding subscription, singpolyma3: "The coding plan is gone now right?" News – Item ; gardnr recalled the final era of allocations: "Last time I got one, I had to log into a Discord server and wait for 'the drop' and IIRC Daniel Kim was giving them out based on who was there at the time. They were gone in less than a minute." News – Item
• On context size, tacone: "the context size they allow for Qwen is just 128k. Still interesting as a specialized sub-agent but not really well suited for long tasks." News – Item ; srcreigh reported a real agent task using 250K context on local hardware: "That's not enough context even for some one shot xhigh requests." News – Item
• On reliability, hexa00: "Input doesn't look faster than other models... Output is awesome, super fast as you expect from the 1500t/sec... Tool call is failing more than say DS4, which leads to time wasted on retries" News – Item
• Summing up the sentiment, olivermuty: "Cerebras the tech is awesome, cerebras the company is a trainwreck" News – Item

CS-4 announcement: 464 points, 275 comments (August 19, shaping September)

The thread (News – Item) focused on hardware credibility and the open-model gap.

• gpm criticized the model catalog: "it is bizarre that they're advertising old open-weight models. GLM 4.7 (December 2025) not 5 (Feb) 5.1 (April) or 5.2 (June)." News – Item
• KronisLV: "God I wish they'd back up all of those claims by offering a subscription of Kimi K3 and GLM 5.3, not some outdated GLM 4.7 instance that they then proceed to call a preview model and say that they'll remove it, leaving users only with GPT-OSS 120B which is nigh useless nowadays" News – Item
• bearjaws asked for exactly what later shipped: "If they could launch Qwen 27b or Deepseek Flash that would be amazing." News – Item
• denizay flagged the undisclosed comparison basis: "The exact GPU models, GPU count, power consumption, price information are not disclosed. We still don't know if buying a multi-GPU rack (or racks) is cheaper and/or more efficient in power." News – Item
• xmorse: "Cerebras is very fast but you can basically never use it because of its scarcity" News – Item

Smaller signals

The Register's "Nvidia and Cerebras are selling performance their customers will probably never see" (Aug 27) drew 6 points and no comments on HN (News – Item). An Ask-adjacent observation from the launch thread worth tracking: anthonypasq speculated "almost of their business is hosting Sol ultra fast or whatever for OpenAI to use internally" (News – Item), consistent with the OpenAI Master Relationship Agreement named in Cerebras's own forward-looking statements (Cerebras – Ultrafast Frontier Inference Cerebras Deep Dive At Hot Chips 2026). Reddit search for Cerebras community signals was blocked by a login wall this cycle and could not be used.

Reddit recovery (added 2026-10-03)

No Cerebras posts in the month's top results; the r/CerebrasSystems community counts 1.6K weekly visitors (captured 2026-10-03). Reddit – Cerebrassystems

Enterprise Readiness

Transparency Gaps

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*Sources: All pricing, rate-limit, model, and caching data from Cerebras – Pricing (accessed via browser 2026-09-30/10-03), Inference-Docs – Overview , Inference-Docs – Qwen 3.8 27B , Inference-Docs – Openai Oss , Inference-Docs – Rate Limits , and Inference-Docs – Prompt Caching (accessed 2026-10-03, reflecting state as of 2026-09-30). News from Cerebras and Cerebras – General Compute Selects Cerebras To Bring Ultra Fast Inference To Agentic Coding . Community signals from Hacker News via Algolia API. Reddit search blocked (login wall).*