Model comparison
Mercury 2.5 vs Mistral Large
Mercury 2.5 is the stronger model overall, scoring 33.5 to 31.9 on the Noometry Index.
Last verified . 3 shared benchmarks.
Mistral AISummary
- They share 3 benchmarks with published results for both. Mercury 2.5 scores higher in 3 categories and Mistral Large in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Mercury 2.5 leads 22.4 to 15.8.
- Mercury 2.5 is cheaper at $0.04 / $0.15 per million input/output tokens, against $2 / $6 for Mistral Large.
- Mercury 2.5 accepts more context: 260K tokens versus 131K.
- Mistral Large has downloadable open weights; the other is API-only.
Side by side
| Mercury 2.5 | Mistral Large | |
|---|---|---|
| Provider | Inception | Mistral AI |
| Noometry Index | 33.5 | 31.9 |
| Released | 2026-09-08 | 2024-02-26 |
| Weights | Proprietary | Open |
| Context window | 260K | 131K |
| Max output | 66K | 16K |
| Input $ / M tokens | $0.04 | $2 |
| Output $ / M tokens | $0.15 | $6 |
| Results tracked | 4 | 51 |
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Category by category
Coding Mercury 2.5 leads
Mercury 2.5: 39.5 (#156), Mistral Large: 34.3 (#240)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| SciCode | 38.5% | 36.2% |
| ALE-Bench | 301.65 | 264.7 |
| BigCodeBench Instruct | — | 30% |
| LiveBench Coding | — | 47.1% |
| LMArena Coding | — | 1277 |
| BigCodeBench Complete | — | 38.3% |
| HumanEval+ | — | 62.2% |
| MBPP+ | — | 59.5% |
Agentic & Tool Use Not comparable
Mercury 2.5: —, Mistral Large: 28.6 (#89)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 38.4% |
Reasoning Mercury 2.5 leads
Mercury 2.5: 22.4 (#193), Mistral Large: 15.8 (#310)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| CritPt | 0% | 0% |
| SimpleBench | — | 22.5% |
| LiveBench Reasoning | — | 43.5% |
| LMArena Hard Prompts | — | 1257 |
| DTBench | — | 65.1% |
| LiveBench Data Analysis | — | 50.1% |
| LMCA | — | 16.7% |
| Epoch Capabilities Index | — | 128.52 |
| ForecastBench | — | 57.1 |
| LiveBench | — | 48.4% |
Math Mercury 2.5 leads
Mercury 2.5: 23.3 (#272), Mistral Large: 18.2 (#291)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 8.5% |
| ProofBench | 3% | — |
| Omni-MATH | — | 28.1% |
| LiveBench Math | — | 42.5% |
| LMArena Math | — | 1262 |
| MATH Level 5 | — | 50.3% |
| FrontierMath (Feb 2025 set) | — | 0.3% |
Knowledge Not comparable
Mercury 2.5: —, Mistral Large: 30.1 (#230)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| GPQA Diamond | — | 51.3% |
| MMLU-Pro | — | 59.9% |
| Confabulations | — | 21.4% |
| Vectara Hallucination Rate | — | 4.5% |
| GPQA (HELM) | — | 43.5% |
| LMArena Expert | — | 1232 |
| MMLU | — | 80% |
Multilingual Not comparable
Mercury 2.5: —, Mistral Large: 40.0 (#219)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| LMArena Non-English | — | 1237 |
| LMArena Chinese | — | 1240 |
| LMArena French | — | 1325 |
| LMArena German | — | 1254 |
| LMArena Japanese | — | 1188 |
| LMArena Korean | — | 1202 |
| LMArena Russian | — | 1257 |
| LMArena Spanish | — | 1268 |
Instruction Following Not comparable
Mercury 2.5: —, Mistral Large: 67.9 (#191)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| LiveBench Instruction Following | — | 67.9% |
| IFEval | — | 87.7% |
| LMArena Instruction Following | — | 1249 |
Long Context Not comparable
Mercury 2.5: —, Mistral Large: 38.3 (#199)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| LMArena Longer Query | — | 1261 |
Writing & Preference Not comparable
Mercury 2.5: —, Mistral Large: 40.7 (#242)
| Benchmark | Mercury 2.5 | Mistral Large |
|---|---|---|
| LMArena Text | — | 1266 |
| LMArena Creative Writing | — | 1243 |
| Short-Story Creative Writing | — | 69% |
| EQ-Bench Creative Writing | — | 985 |
| WildBench | — | 80.1% |
| LMArena Multi-Turn | — | 1260 |
| LiveBench Language | — | 39.4% |
Frequently asked questions
Is Mercury 2.5 better than Mistral Large?
Mercury 2.5 is the stronger model overall, scoring 33.5 to 31.9 on the Noometry Index.
Which is cheaper, Mercury 2.5 or Mistral Large?
Mercury 2.5 is cheaper. It lists at $0.04 per million input tokens and $0.15 per million output tokens; Mistral Large lists at $2 and $6.
Is Mercury 2.5 or Mistral Large better for coding?
Mercury 2.5 scores higher on coding benchmarks: 39.5 versus 34.3 in the Noometry coding category.
Which has the bigger context window?
Mercury 2.5 does, with 260K tokens against 131K.
How many benchmarks do Mercury 2.5 and Mistral Large share?
3 benchmarks have published results for both models. Mercury 2.5 has 4 scored results on Noometry and Mistral Large has 51.