Model comparison
MAI-Thinking-1 vs Mistral Small 4
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: MAI-Thinking-1 unranked (Not scored); Mistral Small 4 #140 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MAI-Thinking-1 and Mistral Small 4 share 0 comparable benchmark results. 0 of 8 categories are comparable. 13 results are unique to MAI-Thinking-1; 16 to Mistral Small 4.
Updated July 23, 2026- Shared results
- 0
- MAI-Thinking-1 only
- 13
- Mistral Small 4 only
- 16
- Comparable categories
- 0 / 8
Benchmark data for MAI-Thinking-1 and Mistral Small 4 is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MAI-Thinking-1 | Mistral Small 4 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MAI-Thinking-1Not available | Mistral Small 4$0.15 input / $0.6 output | A complete price comparison is not available. |
| Generation speedtokens per second | MAI-Thinking-1Not available | Mistral Small 4175 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | MAI-Thinking-1Not available | Mistral Small 40.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | MAI-Thinking-1256K | Mistral Small 4256K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding5 benchmarks
Reasoning3 benchmarks
Knowledge10 benchmarks
| Benchmark | MAI-Thinking-1 | Mistral Small 4 | Result |
|---|---|---|---|
| GPQASource | 84.2% | — | Not comparable |
| GPQA-DSource | 84.2% | — | Not comparable |
| MMLU-ProSource | 85% | — | Not comparable |
| SimpleQASource | 31% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 19.6% | Not comparable |
| AA-GPQA DiamondSource | — | 76.9% | Not comparable |
| AA-HLESource | — | 9.5% | Not comparable |
| AA-Omniscience IndexSource | — | -29.9% | Not comparable |
| AA-Omniscience AccuracySource | — | 22.1% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 66.8% | Not comparable |
Math3 benchmarks
Multimodal1 benchmarks
| Benchmark | MAI-Thinking-1 | Mistral Small 4 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | — | 56.8% | Not comparable |
Frequently Asked Questions (3)
Can I compare MAI-Thinking-1 and Mistral Small 4 on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for MAI-Thinking-1 and Mistral Small 4 today?
Mistral Small 4: $0.15 input / $0.60 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
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