Mercury 2 vs Mistral Medium 3
Mercury 2 leads Mistral Medium 3 on the Artificial Analysis Intelligence Index, 10.8 to 9.0, and Mercury 2 costs 2.7x less per output token ($0.75 vs $2.00 per million). Updated October 21, 2026; 32 benchmarks have a result for both.
Mercury 2 or Mistral Medium 3: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Pick Mercury 2 for output tokens 2.7x cheaper ($0.75 vs $2.00 per million) and work measured by LMArena Text: software and IT or LMArena Text: hard prompts, where it leads.
- Shared results
- 32
- Mercury 2 only
- 10
- Mistral Medium 3 only
- 25
- Like-for-like categories
- 7 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
Neither has a coding score yet.
One side not measured
Intelligence
AA Intelligence Index
Mercury 2
Mercury 2 leads, 10.8 against 9.0.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mercury 2 has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
Mistral Medium 3
Mistral Medium 3 leads, 1079 against 1036.
Same board, both measured
Long documents
Listed context window
Mistral Medium 3
Mistral Medium 3 takes 131K tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mercury 2
Mercury 2 $0.0006, Mistral Medium 3 $0.0014 per turn.
List prices
At a glance
- Coding index
- Mercury 2 not benchmarked, Mistral Medium 3 not benchmarked.
- Widest category
- Agentic work, 46.5 points apart on average over 1 shared benchmark.
- Widest single gap
- τ²-Bench Telecom: Mercury 2 70.8% against Mistral Medium 3 24.3%, 46.5 points apart on a 0 to 100 scale.
- Output price
- Mercury 2 $0.75 against Mistral Medium 3 $2.00 per million output tokens, 2.7x apart.
- Context window
- Mercury 2 takes 128K tokens, Mistral Medium 3 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 | Bars | Mistral Medium 3 | Ties |
|---|---|---|---|---|
| Coding | 2 | 1 | ||
| Intelligence | 1 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 3 | 2 | ||
| Knowledge | 0 | 3 | ||
| Web design | 0 | 6 | ||
| General | 3 | 10 | ||
| All shared boards | 10 | 22 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index21
| Benchmark | Mercury 2 | Mistral Medium 3 | Leader |
|---|---|---|---|
| LMArena WebDev | 1171 | Not measured | Only Mercury 2 measured |
| AA Coding Index | 31.1 | Not measured | Only Mercury 2 measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 40.0% | Only Mistral Medium 3 measured |
| SciCode | 37.7% | Not measured | Only Mercury 2 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | 3.8% | Mercury 2 |
| WeirdML | 43.2% | Not measured | Only Mercury 2 measured |
| ALE-Bench | 785.6 | Not measured | Only Mercury 2 measured |
| LMArena Text: coding | 1390 | 1385 | Mercury 2 |
| LMArena Text: software and IT | 1385 | 1385 | Mistral Medium 3 |
| LMArena WebDev: React | 1160 | Not measured | Only Mercury 2 measured |
| LMArena WebDev: HTML | 1199 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 28 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2 | Mistral Medium 3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 10.8 | 9.0 | Mercury 2 |
| Epoch Capabilities Index | Not measured | 134.0 | Only Mistral Medium 3 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mercury 2 | Mistral Medium 3 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Mercury 2 measured |
| τ²-Bench Telecom | 70.8% | 24.3% | Mercury 2 |
| Neither model has a result on the other 39 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index32
| Benchmark | Mercury 2 | Mistral Medium 3 | Leader |
|---|---|---|---|
| GPQA Diamond (Artificial Analysis run) | 77.0% | 57.8% | Mercury 2 |
| Humanity's Last Exam (Artificial Analysis run) | 17.1% | 4.1% | Mercury 2 |
| LMArena Text: hard prompts | 1362 | 1364 | Mistral Medium 3 |
| LMArena Text: expert | 1358 | 1342 | Mercury 2 |
| LMArena Text: hard prompts in English | 1374 | 1374 | Mistral Medium 3 |
| LMArena Vision: diagrams | Not measured | 1155 | Only Mistral Medium 3 measured |
| LMArena Vision: homework | Not measured | 1165 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Mercury 2 | Mistral Medium 3 | Leader |
|---|---|---|---|
| AA Math Index | Not measured | 30.3 | Only Mistral Medium 3 measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 30.3% | Only Mistral Medium 3 measured |
| LMArena Text: math | Not measured | 1353 | Only Mistral Medium 3 measured |
| LMArena Text: mathematical work | Not measured | 1354 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 9 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mercury 2 | Mistral Medium 3 | Leader |
|---|---|---|---|
| MMLU Pro (Artificial Analysis run) | Not measured | 76.0% | Only Mistral Medium 3 measured |
| LMArena Text: science | 1343 | 1381 | Mistral Medium 3 |
| LMArena Text: medicine and healthcare | 1363 | 1381 | Mistral Medium 3 |
| LMArena Text: legal and government | Not measured | 1384 | Only Mistral Medium 3 measured |
| LMArena Text: business and finance | 1349 | 1352 | Mistral Medium 3 |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Mercury 2 | Mistral Medium 3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1036 | 1079 | Mistral Medium 3 |
| Design Arena: UI components | 998 | 1024 | Mistral Medium 3 |
| Design Arena: game dev | 985 | 1018 | Mistral Medium 3 |
| Design Arena: data viz | 1009 | 1034 | Mistral Medium 3 |
| Design Arena: 3D | 983 | 1084 | Mistral Medium 3 |
| Design Arena: all code categories | 1022 | 1069 | Mistral Medium 3 |
| Design Arena: SVG | 998 | Not measured | Only Mercury 2 measured |
| Design Arena: ASCII art | 988 | Not measured | Only Mercury 2 measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index310
| Benchmark | Mercury 2 | Mistral Medium 3 | Leader |
|---|---|---|---|
| IFBench | 69.8% | 39.3% | Mercury 2 |
| Long context reasoning (AA-LCR) | 43.7% | 31.3% | Mercury 2 |
| DTBench | Not measured | 62.3% | Only Mistral Medium 3 measured |
| LMArena Text | 1354 | 1370 | Mistral Medium 3 |
| LMArena Text: instruction following | 1328 | 1338 | Mistral Medium 3 |
| LMArena Text: creative writing | 1286 | 1343 | Mistral Medium 3 |
| LMArena Vision | Not measured | 1157 | Only Mistral Medium 3 measured |
| LMArena Text: English | 1378 | 1385 | Mistral Medium 3 |
| LMArena Text: non-English | 1330 | 1353 | Mistral Medium 3 |
| LMArena Text: Chinese | 1414 | 1374 | Mercury 2 |
| LMArena Text: German | Not measured | 1377 | Only Mistral Medium 3 measured |
| LMArena Text: Japanese | Not measured | 1316 | Only Mistral Medium 3 measured |
| LMArena Text: Korean | Not measured | 1304 | Only Mistral Medium 3 measured |
| LMArena Text: French | Not measured | 1368 | Only Mistral Medium 3 measured |
| LMArena Text: Spanish | Not measured | 1364 | Only Mistral Medium 3 measured |
| LMArena Text: Russian | 1304 | 1359 | Mistral Medium 3 |
| LMArena Text: Polish | Not measured | 1371 | Only Mistral Medium 3 measured |
| LMArena Text: multi-turn | 1357 | 1384 | Mistral Medium 3 |
| LMArena Text: longer queries | 1329 | 1360 | Mistral Medium 3 |
| LMArena Text: writing and language | 1300 | 1352 | Mistral Medium 3 |
| LMArena Text: entertainment and media | 1314 | 1335 | Mistral Medium 3 |
| LMArena Vision: English | Not measured | 1172 | Only Mistral Medium 3 measured |
| LMArena Vision: Chinese | Not measured | 1161 | Only Mistral Medium 3 measured |
| LMArena Vision: reading text | Not measured | 1154 | Only Mistral Medium 3 measured |
| LMArena Vision: humor | Not measured | 1145 | Only Mistral Medium 3 measured |
| LMArena Vision: captioning | Not measured | 1094 | Only Mistral Medium 3 measured |
| LMArena Vision: recognizing things | Not measured | 1141 | Only Mistral Medium 3 measured |
| LMArena Vision: creative writing | Not measured | 1146 | Only Mistral Medium 3 measured |
| Neither model has a result on the other 18 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mercury 2 | Mistral Medium 3 | 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 costs less
Repository review
50K input + 3K output tokens
Mercury 2 costs less
Agent loop
200K input + 10K output tokens
Mercury 2 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 | Mistral Medium 3 |
|---|---|---|
| Maker | Inception | Mistral AI |
| Weights | No public weights listed | No public weights listed |
| Released | March 4, 2026 | May 7, 2025 |
| Context window | 128K | 131K |
| Input $/Mtok | $0.25 | $0.40 |
| Output $/Mtok | $0.75 | $2.00 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 1 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mercury 2 better than Mistral Medium 3 for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Pick Mercury 2 for output tokens 2.7x cheaper ($0.75 vs $2.00 per million) and work measured by LMArena Text: software and IT or LMArena Text: hard prompts, where it leads.
Which is cheaper, Mercury 2 or Mistral Medium 3?
Mercury 2 costs $0.25 per million input tokens and $0.75 per million output tokens; Mistral Medium 3 costs $0.40 and $2.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Mercury 2 or Mistral Medium 3?
Mistral Medium 3, with 131K tokens against 128K.
How many benchmarks is the Mercury 2 vs Mistral Medium 3 comparison based on?
32 benchmarks have a result for both models as of October 21, 2026. Mercury 2's coding index rests on 1 independent benchmark and Mistral Medium 3's on 0. Where only one model has a result, the page says so instead of naming a winner.