Mercury 2.5 vs Mistral Medium 3.1
Mercury 2.5 leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 12.3 to 9.2, and Mercury 2.5 costs 13.3x less per output token ($0.15 vs $2.00 per million). Updated October 22, 2026; 6 benchmarks have a result for both.
Mercury 2.5 or Mistral Medium 3.1: which to pick
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
- Shared results
- 6
- Mercury 2.5 only
- 16
- Mistral Medium 3.1 only
- 68
- Like-for-like categories
- 5 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Mercury 2.5 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Mercury 2.5
Mercury 2.5 leads, 12.3 against 9.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.1 has a AA Agentic Index result, 1.9.
Directional only
Math
AIME
No call
Only Mistral Medium 3.1 has a AIME result, 42.3%.
Directional only
Knowledge
MMLU Pro
No call
Only Mistral Medium 3.1 has a MMLU Pro result, 75.3%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Medium 3.1 has a Design Arena: websites result, 1132.
Directional only
Long documents
Listed context window
Mercury 2.5
Mercury 2.5 takes 260K tokens against 131K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2.5
Mercury 2.5 $0.0001, Mistral Medium 3.1 $0.0014 per turn.
List prices
At a glance
- Coding index
- Mercury 2.5 1.6 from 2 benchmarks, Mistral Medium 3.1 not benchmarked.
- Widest category
- General, 29.0 points apart on average over 1 shared benchmark.
- Widest single gap
- Long context reasoning (AA-LCR): Mercury 2.5 71.7% against Mistral Medium 3.1 42.7%, 29.0 points apart on a 0 to 100 scale.
- Output price
- Mercury 2.5 $0.15 against Mistral Medium 3.1 $2.00 per million output tokens, 13.3x apart.
- Context window
- Mercury 2.5 takes 260K tokens, Mistral Medium 3.1 131K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Mercury 2.5 | Bars | Mistral Medium 3.1 | Ties |
|---|---|---|---|---|
| Coding | 2 | 0 | ||
| Intelligence | 1 | 0 | ||
| Reasoning | 1 | 0 | ||
| Knowledge | 1 | 0 | ||
| General | 1 | 0 | ||
| All shared boards | 6 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index20
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| AA Coding Index | Not measured | 20.5 | Only Mistral Medium 3.1 measured |
| LiveCodeBench (Vals AI) | Not measured | 44.8% | Only Mistral Medium 3.1 measured |
| Terminal-Bench 4 (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| Vibe Code Bench (Vals AI) | 3.7% | Not measured | Only Mercury 2.5 measured |
| Code migration (Vals AI) | 4.5% | Not measured | Only Mercury 2.5 measured |
| IOI (Vals AI) | 2.4% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 34.5% | Not measured | Only Mercury 2.5 measured |
| SkillsBench (Vals AI) | 18.1% | Not measured | Only Mercury 2.5 measured |
| CyberBench (Vals AI) | 45.5% | Not measured | Only Mercury 2.5 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 40.6% | Only Mistral Medium 3.1 measured |
| SciCode | 38.5% | 32.4% | Mercury 2.5 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 10.6% | Only Mistral Medium 3.1 measured |
| ALE-Bench | 301.6 | 210.2 | Mercury 2.5 |
| LMArena Text: coding | Not measured | 1433 | Only Mistral Medium 3.1 measured |
| LMArena Text: software and IT | Not measured | 1436 | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 24 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.3 | 9.2 | Mercury 2.5 |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 1.9 | Only Mistral Medium 3.1 measured |
| Finance Agent (Vals AI) | 18.9% | Not measured | Only Mercury 2.5 measured |
| Tax Agent Bench (Vals AI) | 2.5% | Not measured | Only Mercury 2.5 measured |
| Legal Research Bench (Vals AI) | 4.3% | Not measured | Only Mercury 2.5 measured |
| Excel Modeling Benchmark (Vals AI) | 8.8% | Not measured | Only Mercury 2.5 measured |
| Terminal-Bench-Science (Vals AI) | 0.0% | Not measured | Only Mercury 2.5 measured |
| τ²-Bench Telecom | Not measured | 40.6% | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 34 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| MMMU Pro (Vals AI) | Not measured | 63.0% | Only Mistral Medium 3.1 measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 58.8% | Only Mistral Medium 3.1 measured |
| Humanity's Last Exam (Artificial Analysis run) | 11.8% | 4.7% | Mercury 2.5 |
| LMArena Text: hard prompts | Not measured | 1426 | Only Mistral Medium 3.1 measured |
| LMArena Text: expert | Not measured | 1408 | Only Mistral Medium 3.1 measured |
| LMArena Text: hard prompts in English | Not measured | 1435 | Only Mistral Medium 3.1 measured |
| LMArena Vision: diagrams | Not measured | 1175 | Only Mistral Medium 3.1 measured |
| LMArena Vision: homework | Not measured | 1165 | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 14 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| AIME | Not measured | 42.3% | Only Mistral Medium 3.1 measured |
| MATH 500 (Vals AI) | Not measured | 87.0% | Only Mistral Medium 3.1 measured |
| MGSM (Vals AI) | Not measured | 90.9% | Only Mistral Medium 3.1 measured |
| AA Math Index | Not measured | 38.3 | Only Mistral Medium 3.1 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 38.3% | Only Mistral Medium 3.1 measured |
| ProofBench | 3.0% | Not measured | Only Mercury 2.5 measured |
| LMArena Text: math | Not measured | 1408 | Only Mistral Medium 3.1 measured |
| LMArena Text: mathematical work | Not measured | 1412 | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 75.3% | Only Mistral Medium 3.1 measured |
| LegalBench (Vals AI) | 83.1% | 62.0% | Mercury 2.5 |
| CorpFin (Vals AI) | Not measured | 50.7% | Only Mistral Medium 3.1 measured |
| TaxEval (Vals AI) | Not measured | 70.3% | Only Mistral Medium 3.1 measured |
| MortgageTax (Vals AI) | Not measured | 36.5% | Only Mistral Medium 3.1 measured |
| MedQA (Vals AI) | Not measured | 78.2% | Only Mistral Medium 3.1 measured |
| MedCode (Vals AI) | 31.3% | Not measured | Only Mercury 2.5 measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 68.3% | Only Mistral Medium 3.1 measured |
| LMArena Text: science | Not measured | 1444 | Only Mistral Medium 3.1 measured |
| LMArena Text: medicine and healthcare | Not measured | 1449 | Only Mistral Medium 3.1 measured |
| LMArena Text: legal and government | Not measured | 1439 | Only Mistral Medium 3.1 measured |
| LMArena Text: business and finance | Not measured | 1418 | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 6 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1132 | Only Mistral Medium 3.1 measured |
| Design Arena: UI components | Not measured | 1097 | Only Mistral Medium 3.1 measured |
| Design Arena: game dev | Not measured | 1073 | Only Mistral Medium 3.1 measured |
| Design Arena: data viz | Not measured | 1144 | Only Mistral Medium 3.1 measured |
| Design Arena: 3D | Not measured | 1081 | Only Mistral Medium 3.1 measured |
| Design Arena: all code categories | Not measured | 1120 | Only Mistral Medium 3.1 measured |
| Design Arena: SVG | Not measured | 992 | Only Mistral Medium 3.1 measured |
| Design Arena: ASCII art | Not measured | 997 | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| Public Benefits Bench (Vals AI) | 45.3% | Not measured | Only Mercury 2.5 measured |
| MedScribe (Vals AI) | 55.1% | Not measured | Only Mercury 2.5 measured |
| IFBench | Not measured | 39.8% | Only Mistral Medium 3.1 measured |
| Long context reasoning (AA-LCR) | 71.7% | 42.7% | Mercury 2.5 |
| DTBench | Not measured | 67.5% | Only Mistral Medium 3.1 measured |
| LMCA | Not measured | 19.1% | Only Mistral Medium 3.1 measured |
| LMArena Text | Not measured | 1424 | Only Mistral Medium 3.1 measured |
| LMArena Text: instruction following | Not measured | 1398 | Only Mistral Medium 3.1 measured |
| LMArena Text: creative writing | Not measured | 1391 | Only Mistral Medium 3.1 measured |
| LMArena Vision | Not measured | 1172 | Only Mistral Medium 3.1 measured |
| LMArena Text: English | Not measured | 1438 | Only Mistral Medium 3.1 measured |
| LMArena Text: non-English | Not measured | 1408 | Only Mistral Medium 3.1 measured |
| LMArena Text: Chinese | Not measured | 1447 | Only Mistral Medium 3.1 measured |
| LMArena Text: German | Not measured | 1432 | Only Mistral Medium 3.1 measured |
| LMArena Text: Japanese | Not measured | 1379 | Only Mistral Medium 3.1 measured |
| LMArena Text: Korean | Not measured | 1380 | Only Mistral Medium 3.1 measured |
| LMArena Text: French | Not measured | 1460 | Only Mistral Medium 3.1 measured |
| LMArena Text: Spanish | Not measured | 1433 | Only Mistral Medium 3.1 measured |
| LMArena Text: Russian | Not measured | 1411 | Only Mistral Medium 3.1 measured |
| LMArena Text: Polish | Not measured | 1430 | Only Mistral Medium 3.1 measured |
| LMArena Text: multi-turn | Not measured | 1418 | Only Mistral Medium 3.1 measured |
| LMArena Text: longer queries | Not measured | 1406 | Only Mistral Medium 3.1 measured |
| LMArena Text: writing and language | Not measured | 1395 | Only Mistral Medium 3.1 measured |
| LMArena Text: entertainment and media | Not measured | 1390 | Only Mistral Medium 3.1 measured |
| LMArena Vision: English | Not measured | 1179 | Only Mistral Medium 3.1 measured |
| LMArena Vision: Chinese | Not measured | 1190 | Only Mistral Medium 3.1 measured |
| LMArena Vision: reading text | Not measured | 1175 | Only Mistral Medium 3.1 measured |
| LMArena Vision: humor | Not measured | 1168 | Only Mistral Medium 3.1 measured |
| LMArena Vision: captioning | Not measured | 1145 | Only Mistral Medium 3.1 measured |
| LMArena Vision: recognizing things | Not measured | 1147 | Only Mistral Medium 3.1 measured |
| LMArena Vision: creative writing | Not measured | 1200 | Only Mistral Medium 3.1 measured |
| Neither model has a result on the other 15 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2.5 | Mistral Medium 3.1 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Mercury 2.5 costs less
Repository review
50K input + 3K output tokens
Mercury 2.5 costs less
Agent loop
200K input + 10K output tokens
Mercury 2.5 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Inception Mercury 2.5 | Mistral Medium 3.1 |
|---|---|---|
| Maker | Inception | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | September 8, 2026 | August 13, 2025 |
| Context window | 260K | 131K |
| Input $/Mtok | $0.04 | $0.40 |
| Output $/Mtok | $0.15 | $2.00 |
| Coding index | 1.6 | Not benchmarked |
| Independent measurements behind it | 2 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2.5 better than Mistral Medium 3.1 for coding?
Only Mercury 2.5 has a coding score, 1.6 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Mercury 2.5 or Mistral Medium 3.1?
Mercury 2.5 costs $0.04 per million input tokens and $0.15 per million output tokens; Mistral Medium 3.1 costs $0.40 and $2.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2.5 or Mistral Medium 3.1?
Mercury 2.5, with 260K tokens against 131K.
How many benchmarks is the Mercury 2.5 vs Mistral Medium 3.1 comparison based on?
6 benchmarks have a result for both models as of October 22, 2026. Mercury 2.5's coding index rests on 2 independent benchmarks and Mistral Medium 3.1's on 0. Where only one model has a result, the page says so instead of naming a winner.