Large-scale reasoning model with a 1M-token context for long-horizon agents and project-level engineering.
Top open-weight models. The cheapest way to run them.
Kimi, GLM, DeepSeek, GPT OSS, MiniMax, and Qwen behind one gateway that speaks your existing OpenAI or Anthropic SDK. Prepaid, so spend can never run past budget. Pay per token — nothing else.
Coding-focused agentic model built for reliable end-to-end software engineering across long contexts.
Flagship MoE reasoning model for advanced coding, long-context analysis, and complex agent workflows.
Sparse-attention multimodal model suited to coding agents, document-heavy workflows, and multi-step reasoning.
Native multimodal agent model for long-horizon coding, UI generation, tool use, and agentic workflows.
Cost-effective multimodal agent model for coding, screenshot-driven workflows, tool use, and planning.
Efficiency-optimized MoE model for fast, cost-effective reasoning, coding, and agents over 1M-token contexts.
OpenAI's open-weight MoE model for high-reasoning, agentic, and production workloads with function calling.
The models teams are reaching for.
A curated lineup of the best open weights — including these, live right now. New frontier releases land here days after they ship, with per-token pricing shown in the console.
Kimi K2.6
Moonshot AINative multimodal agent model for long-horizon coding, UI generation, tool use, and agentic workflows.
Kimi K2.7 Code
Moonshot AICoding-focused agentic model built for reliable end-to-end software engineering across long contexts.
GLM 5.2
Z.aiLarge-scale reasoning model with a 1M-token context for long-horizon agents and project-level engineering.
DeepSeek V4 Flash
DeepSeekEfficiency-optimized MoE model for fast, cost-effective reasoning, coding, and agents over 1M-token contexts.
DeepSeek V4 Pro
DeepSeekFlagship MoE reasoning model for advanced coding, long-context analysis, and complex agent workflows.
GPT OSS 120B
OpenAIOpenAI's open-weight MoE model for high-reasoning, agentic, and production workloads with function calling.
MiniMax M3
MiniMaxSparse-attention multimodal model suited to coding agents, document-heavy workflows, and multi-step reasoning.
Qwen3.7 Plus
AlibabaCost-effective multimodal agent model for coding, screenshot-driven workflows, tool use, and planning.
And the list keeps growing. New frontier open weights go live days after release — you never wait on a roadmap to run the latest model.
Three lines to switch. Keep the rest of your code.
The gateway is compatible with the APIs you already use. Point your SDK at your Chompute base URL, add your access key, and pick a model — streaming, tool calling, and structured outputs included.
- ✓OpenAI Chat Completions, OpenAI Responses, and Anthropic Messages
- ✓Drop-in over your existing SDK — no rewrite, no new dependencies
- ✓Streaming, function/tool calling, and structured outputs supported
- ✓Reasoning controls per model — thinking budgets, effort levels
01from openai import OpenAI0203client = OpenAI(04 base_url="YOUR_GATEWAY_URL/v1", # shown in your console05 api_key="unused", # auth is the header below06 default_headers={"X-Chompute-Access-Key": "YOUR_ACCESS_KEY"},07)0809stream = client.chat.completions.create(10 model="kimi-k2.7-code",11 messages=[{"role": "user", "content": "Refactor this handler."}],12 stream=True,13)1415for chunk in stream:16 print(chunk.choices[0].delta.content or "", end="")Why this is the cheapest path.
Open-weight models rewrote the price of intelligence. Chompute is built to pass that price through, not mark it up.
Open weights closed the gap.
The best open-weight models now sit next to closed frontier models on the benchmarks that matter — coding, tool use, long-horizon agents — at a fraction of the per-token price.
The cheapest way to run them.
Chompute serves top open-weight models at the lowest per-token cost. Live pricing for every model is in the console — the price you see is the price you pay.
Pay for tokens. Nothing else.
No platform fee, no seats, no minimum commitment. Your balance only moves when you call the API.
Spend that can't surprise you.
Prepaid is not a limitation — it is the point. Your balance is a hard ceiling that no agent, no team, and no runaway loop can break through.
Prepaid by design.
Top up $5, $50, or $100. Requests draw down the balance, and spending stops at zero — you can never go over budget. No card on file quietly running up an invoice.
Every token attributed.
Live usage insights in the console — requests, tokens, and cost per model — so you always know exactly where spend is going.
Keys per team or project.
Issue separate API keys per team, app, or environment — and track usage against each key.
Sign in to streaming tokens in minutes.
Sign in
Google sign-in and you are in the console. No sales call, no procurement cycle, no card required to look around.
Add balance
Start with $5 through Stripe checkout. Your balance is your hard budget ceiling — top up only when you choose to.
Point your SDK
Swap the base URL, add your access key, keep your code. Your first tokens stream back in minutes.
Starts like a tool. Governs like a platform.
Chompute Inference runs under the Chompute AI Control Plane. The endpoint one developer adopts in an afternoon carries the attribution, budgets, and audit trail an organization needs later — nothing to migrate.
- ✓Same access layer and audit trail as every governed AI surface
- ✓Usage attribution ready for finance and platform reviews
- ✓Concurrency and spend controls per account
- ✓Scales from one developer to org-wide policy on the control plane
Questions, answered.
Will it work with my existing code?
Which models do I get?
How does the prepaid billing work?
What happens if my balance runs out?
Why not just show prices on this page?
Can I create multiple API keys?
What about enterprise volume or governance?
Run top open-weight models in minutes.
Sign in, add $5, point your SDK. No subscription, no platform fee, no way to go over budget.