For coding agents, Devstral 2 and MiniMax M3 cost about the same per request ($0.010 vs $0.010 on our measured traffic).
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| Cost at list price | MiniMax M3 | Devstral 2 |
|---|---|---|
| Prompt under 100K tokens50% of requests, 87% of input cached | $0.0060 | $0.0062 |
| Prompt of 100K to 272K39% of requests, 88% of input cached | $0.015 | $0.015 |
| Prompt over 272K tokens11% of requests, 86% of input cached | n/a | n/a |
| Average request | $0.010 | $0.010 |
| 100 requests | $1.00 | $1.01 |
| Median session16 requests; a session ends after 10 idle minutes | $0.12 | $0.12 |
| A month of regular usemedian of 20 users active on 5+ days | $12.82 | $12.73 |
Each logged request priced at the listed rates above for its own token counts, including cache reads and any higher rate for long prompts. Average output: 698 tokens per request. Both models are priced on the requests up to 262K tokens that fit in both context windows; band shares above describe all requests.
| Artificial Analysis | MiniMax M3 | Devstral 2 |
|---|---|---|
| Intelligence Index10 evaluations, 0 to 100 | 29 | 9 |
| Terminal-Bench 4.0agentic coding in a terminal | 2.0% | 0.0% |
| Output speedmedian | 119 tokens/s | n/a |
| Time to first answer tokenincludes thinking time | 18 s | n/a |
Source: Artificial Analysis (artificialanalysis.ai). Measured variants: MiniMax-M3, speed on MiniMax; Devstral 2. Fetched October 13, 2026. Artificial Analysis runs Terminal-Bench 4.0 in its own setup, so its scores differ from the tbench.ai leaderboard.
Devstral 2's 262K window cannot take 12% of coding-agent requests, so the comparison uses only requests both can take. The price is OpenRouter's listed rate on October 13, 2026, which can be a third-party host's; MiniMax's own API may charge differently. MiniMax M3 scores as well or better on the benchmarks above, so the cheaper request is not bought with much lower ability.
Pick a winner in each dimension. You can change your vote any time. 2 votes cast so far.
Correctness and depth of what it produces
Tool calls, instruction-following, and multi-step tasks
Tokens per second and time-to-first-token
How much capability you get per dollar
Consistent results: fewer refusals, loops and format breaks
Setting it up? MiniMax M3: model ID, providers and agent config
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Current Claude, GPT, Gemini and open models run on Standard Compute