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Run OpenCode, Aider, Cursor, and more on Europe's fastest AI platform. Full precision. No quantization. No compromises.
What is Agentic Coding?
Agentic coding tools like Cursor, Cline, and Codex CLI work differently from chat interfaces. Instead of answering questions, they read your codebase, plan changes, apply patches, run tests, inspect errors, and iterate until the work is done - often executing 50 to 200+ turns per task. This makes inference speed critical: every extra 100ms per turn compounds across hundreds of iterations, turning a 10-minute task into an hour-long wait.
MiniMax M2.7 Ultraspeed on Infercom delivers 400+ tokens per second while matching frontier model performance on coding benchmarks. Whether you're using it as a full replacement or splitting planning and execution across providers, fast inference means faster iteration cycles, lower costs, and more responsive coding workflows.
400+ tok/s
Measured on our production API in Munich. Less waiting, more coding.
How dataflow architecture enables ultrafast inference€0.60 / €2.40
Per 1M tokens (input/output), excl. VAT. Pay only for the tokens your agents use.
EU Sovereign
Data processed in Germany. Zero data retention - no training on your data.
Scale Without Surprises
Transparent pay-as-you-go pricing. Know exactly what you'll pay before you start.
Two Ways to Run Agentic Coding on Infercom
Replace your frontier model entirely, or keep it for planning and offload execution
MiniMax M2.7 Ultraspeed matches frontier models on coding benchmarks at a fraction of the cost. You can use it for everything - or split the load between planning and execution.
Full Replacement
Use MiniMax M2.7 Ultraspeed for everything
- Simplest setup - one model, one provider
- 56% SWE-Pro - matches frontier performance
- 400+ tokens/sec on EU infrastructure
Best for: Cost-conscious teams, high-volume workloads
Planner/Executor Split
Keep your frontier model for planning
- Planning: Claude, GPT, or Gemini (5-15 turns)
- Execution: MiniMax M2.7 Ultraspeed on Infercom (50-200+ turns)
- Best of both - frontier reasoning + fast execution
Best for: Teams already invested in frontier models
Both options run on EU sovereign infrastructure with full GDPR compliance. Tools with native support: Codex CLI, Cline, OpenCode, Cursor, and more.
See Configuration GuidesWhy Fast Inference Matters for Coding Agents
Agentic workflows are iteration-heavy. Speed directly impacts productivity and cost.
Execution Dominates
Coding agents spend 80-95% of their turns on execution - file reads, edits, test runs, retries. A 4x speedup on execution means 3-4x faster overall task completion.
Tokens Add Up Fast
Every call in an agentic loop resends the growing conversation, so a single coding task can send hundreds of thousands of input tokens. That makes the price per token the number to watch: €0.60 input and €2.40 output per million tokens on Infercom, excl. VAT.
Faster Feedback Loops
When each iteration returns in seconds instead of minutes, you can review, adjust, and re-run more frequently. Speed enables tighter human-in-the-loop workflows.
Built for Agentic Workflows
MiniMax M2.7 Ultraspeed delivers frontier-level coding performance with native multi-agent capabilities
56%
SWE-Pro
Professional software engineering
76.5%
SWE Multilingual
Cross-language coding
57%
Terminal Bench 2
CLI and system tasks
66.6%
MLE Bench Lite
ML engineering competitions
"MiniMax M2.7 Ultraspeed achieved a 30% performance improvement through autonomous iteration cycles - analyzing, planning, modifying, and evaluating code without human intervention."
- SambaNova Blog
Works With Your Favorite Tools
Drop-in replacement via OpenAI-compatible API. Switch in minutes.
These tools are developed by their respective creators. Infercom is not affiliated with or endorsed by these projects.
See It In Action
Real agentic coding with MiniMax M2.7 Ultraspeed on EU infrastructure
OpenCode with MiniMax M2.7 Ultraspeed on Infercom - reasoning, tool calling, and file operations at 400+ tokens/secClick to enlarge
Developers Are Moving to Open-Weight Models
Three independent signals from 2025 and 2026.
1/3
of tokens on open-weight models
By late 2025, open-weight models handled about a third of all tokens on OpenRouter. Coding grew from 11% to more than half of all tokens in the same year.OpenRouter and a16z, State of AI (Jan 2026)
60-70%
AT&T's target for open models
AT&T already sends 40% of employee AI queries to open models. Routing tasks to cheaper models cut its coding costs by up to 56%, with 2% lower quality.The Information, via PYMNTS (Aug 2026)
75.8%
SWE-bench Verified, open-weight
MiniMax M2.5, the predecessor of the model we serve, resolved 75.8% of tasks - one point behind the best closed model (76.8%).SWE-bench leaderboard, bash-only (Feb 2026)
Your code, your prompts, your data - processed entirely on EU infrastructure. No US CLOUD Act exposure.