Model comparison
MiniMax M2.5 vs Mistral Large 3
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: MiniMax M2.5 #55 (Supported); Mistral Large 3 #113 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. MiniMax M2.5 and Mistral Large 3 share 0 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to MiniMax M2.5; 16 to Mistral Large 3.
Updated July 21, 2026- Shared results
- 0
- MiniMax M2.5 only
- 1
- Mistral Large 3 only
- 16
- Comparable categories
- 0 / 8
Benchmark data for MiniMax M2.5 and Mistral Large 3 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.
Mistral Large 3 is priced at $0.50 input / $1.50 output per 1M tokens, versus $0.30 input / $1.20 output per 1M tokens for MiniMax M2.5.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | MiniMax M2.5 | Mistral Large 3 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | MiniMax M2.5$0.3 input / $1.2 output | Mistral Large 3$0.5 input / $1.5 output | MiniMax M2.5 has the lower combined listed price. |
| Generation speedtokens per second | MiniMax M2.546 tok/s | Mistral Large 348 tok/s | Mistral Large 3 has the higher measured throughput. |
| First-answer latencyseconds to first token | MiniMax M2.52.12 s | Mistral Large 31.04 s | Mistral Large 3 reaches the first token sooner. |
| Context windowmaximum listed tokens | MiniMax M2.5128K | Mistral Large 3128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | MiniMax M2.5 | Mistral Large 3 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 15.9% | Not comparable |
| AA-GPQA DiamondSource | — | 68.0% | Not comparable |
| AA-HLESource | — | 4.1% | Not comparable |
| AA-Omniscience IndexSource | — | -39.4% | Not comparable |
| AA-Omniscience AccuracySource | — | 24.1% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 83.7% | Not comparable |
Multimodal1 benchmarks
| Benchmark | MiniMax M2.5 | Mistral Large 3 | Result |
|---|---|---|---|
| AA-MMMU-ProSource | — | 55.7% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | MiniMax M2.5 | Mistral Large 3 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 36.2% | Not comparable |
Frequently Asked Questions (3)
Can I compare MiniMax M2.5 and Mistral Large 3 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 MiniMax M2.5 and Mistral Large 3 today?
MiniMax M2.5: $0.30 input / $1.20 output per 1M tokens Mistral Large 3: $0.50 input / $1.50 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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