Gemini 2.5 Pro vs Mistral Large 4
Mistral Large 4 leads Gemini 2.5 Pro on coding, 56.4 to 19.1 on the Vibe Coding Index, and Mistral Large 4 costs 2.4x less per output token ($4.18 vs $10.00 per million). Updated October 22, 2026; 51 benchmarks have a result for both.
vs boards won of 51 shared
Gemini 2.5 Pro or Mistral Large 4: which to pick
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro.
Pick Gemini 2.5 Pro for work measured by LMArena Text: hard prompts or LMArena Text: expert, where it leads.
Model AGemini 2.5 ProGoogle19.1/1003 independent benchmarks$0.64 per solved taskModel BMistral Large 4Mistral AI56.4/1005 independent benchmarksNo cost per solved task
- Shared results
- 51
- Gemini 2.5 Pro only
- 39
- Mistral Large 4 only
- 30
- 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
Mistral Large 4
Mistral Large 4 scores 56.4 against 19.1.
3 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 16.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Gemini 2.5 Pro has a AA Agentic Index result, 1.6.
Directional only
Web design
Design Arena: websites
Mistral Large 4
Mistral Large 4 leads, 1257 against 1167.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large 4
Gemini 2.5 Pro $0.0063, Mistral Large 4 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 2.5 Pro has the number, $0.64.
Directional only
At a glance
- Coding index
- Gemini 2.5 Pro 19.1 from 3 benchmarks, Mistral Large 4 56.4 from 5 benchmarks.
- Widest category
- Coding, 29.8 points apart on average over 6 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Gemini 2.5 Pro 0.4% against Mistral Large 4 78.4%, 78.0 points apart on a 0 to 100 scale.
- Output price
- Gemini 2.5 Pro $10.00 against Mistral Large 4 $4.18 per million output tokens, 2.4x apart.
- Context window
- Both take 1.05M tokens.
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 | Gemini 2.5 Pro | Bars | Mistral Large 4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 6 | ||
| Intelligence | 0 | 2 | ||
| Reasoning | 3 | 3 | ||
| Math | 0 | 5 | ||
| Knowledge | 5 | 0 | ||
| Web design | 0 | 6 | ||
| General | 13 | 8 | ||
| All shared boards | 21 | 30 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index06
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | Leader |
|---|---|---|---|
| SWE-bench Verified | 53.6% | Not measured | Only Gemini 2.5 Pro measured |
| LiveBench coding | Not measured | 60.0% | Only Mistral Large 4 measured |
| LMArena WebDev | 1226 | 1543 | Mistral Large 4 |
| AA Coding Index | 33.3 | Not measured | Only Gemini 2.5 Pro measured |
| SWE-bench Verified (Vals AI) | 54.4% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 27.8% | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | 0.4% | 78.4% | Mistral Large 4 |
| Code migration (Vals AI) | Not measured | 30.6% | Only Mistral Large 4 measured |
| IOI (Vals AI) | Not measured | 45.3% | Only Mistral Large 4 measured |
| SWE-bench Multimodal (Vals AI) | Not measured | 33.1% | Only Mistral Large 4 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 14.3% | Only Mistral Large 4 measured |
| LiveCodeBench (Artificial Analysis run) | 80.1% | Not measured | Only Gemini 2.5 Pro measured |
| SciCode | 46.3% | 54.2% | Mistral Large 4 |
| Terminal-Bench Hard (Artificial Analysis run) | 26.5% | Not measured | Only Gemini 2.5 Pro measured |
| Terminal-Bench | 32.6% | Not measured | Only Gemini 2.5 Pro measured |
| FrontierCode | Not measured | 39.4% | Only Mistral Large 4 measured |
| GSO-Bench | 3.9% | Not measured | Only Gemini 2.5 Pro measured |
| WeirdML | 54.0% | Not measured | Only Gemini 2.5 Pro measured |
| ALE-Bench | Not measured | 1213.2 | Only Mistral Large 4 measured |
| LMArena Text: coding | 1452 | 1478 | Mistral Large 4 |
| LMArena Text: software and IT | 1459 | 1467 | Mistral Large 4 |
| LMArena WebDev: React | Not measured | 1559 | Only Mistral Large 4 measured |
| LMArena WebDev: HTML | 1235 | 1487 | Mistral Large 4 |
| LMArena WebDev: from an image | 1285 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 16.1 | 38.4 | Mistral Large 4 |
| Epoch Capabilities Index | 145.1 | 150.0 | Mistral Large 4 |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index15 boards, none shared
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Agentic Index | 1.6 | Not measured | Only Gemini 2.5 Pro measured |
| LiveBench research | Not measured | 28.1% | Only Mistral Large 4 measured |
| LiveBench browser | Not measured | 8.0% | Only Mistral Large 4 measured |
| LiveBench long agentic | Not measured | 11.8% | Only Mistral Large 4 measured |
| Finance Agent (Vals AI) | Not measured | 54.7% | Only Mistral Large 4 measured |
| Tax Agent Bench (Vals AI) | Not measured | 30.4% | Only Mistral Large 4 measured |
| Legal Research Bench (Vals AI) | Not measured | 31.7% | Only Mistral Large 4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 17.5% | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 56.2% | Only Mistral Large 4 measured |
| BioMysteryBench (Vals AI) | Not measured | 67.0% | Only Mistral Large 4 measured |
| τ²-Bench Telecom | 54.1% | Not measured | Only Gemini 2.5 Pro measured |
| GDPval | 23.3% | Not measured | Only Gemini 2.5 Pro measured |
| DeepResearch Bench | 41.5% | Not measured | Only Gemini 2.5 Pro measured |
| Vending-Bench 2 | $574 | Not measured | Only Gemini 2.5 Pro measured |
| BrowseComp-Plus | 29.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 26 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index33
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 83.9% | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | Not measured | 12.2% | Only Mistral Large 4 measured |
| GPQA Diamond (Artificial Analysis run) | 84.4% | Not measured | Only Gemini 2.5 Pro measured |
| Humanity's Last Exam (Artificial Analysis run) | 22.5% | 35.0% | Mistral Large 4 |
| GPQA Diamond (Epoch AI run) | 85.3% | 88.1% | Mistral Large 4 |
| ARC-AGI | 41.0% | Not measured | Only Gemini 2.5 Pro measured |
| ARC-AGI-2 | 4.9% | Not measured | Only Gemini 2.5 Pro measured |
| Chess puzzles | Not measured | 33.0% | Only Mistral Large 4 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | 1455 | 1444 | Gemini 2.5 Pro |
| LMArena Text: expert | 1452 | 1444 | Gemini 2.5 Pro |
| LMArena Text: hard prompts in English | 1453 | 1442 | Gemini 2.5 Pro |
| LMArena Vision: diagrams | 1274 | 1288 | Mistral Large 4 |
| LMArena Vision: homework | 1281 | Not measured | Only Gemini 2.5 Pro measured |
| Kagi LLM Benchmark | 70.3% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index05
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Math Index | 87.7 | Not measured | Only Gemini 2.5 Pro measured |
| AIME 2025 (Artificial Analysis run) | 87.7% | Not measured | Only Gemini 2.5 Pro measured |
| OTIS Mock AIME | 84.7% | 98.3% | Mistral Large 4 |
| FrontierMath, tiers 1 to 3 | 24.6% | 58.6% | Mistral Large 4 |
| FrontierMath, tier 4 | 0.0% | 26.8% | Mistral Large 4 |
| ProofBench | Not measured | 10.0% | Only Mistral Large 4 measured |
| LMArena Text: math | 1450 | 1469 | Mistral Large 4 |
| LMArena Text: mathematical work | 1454 | 1462 | Mistral Large 4 |
| Neither model has a result on the other 5 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index50
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | Leader |
|---|---|---|---|
| CaseLaw (Vals AI) | 63.9% | Not measured | Only Gemini 2.5 Pro measured |
| CorpFin (Vals AI) | 60.8% | Not measured | Only Gemini 2.5 Pro measured |
| MortgageTax (Vals AI) | 68.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedCode (Vals AI) | 50.6% | 40.7% | Gemini 2.5 Pro |
| MMLU Pro (Artificial Analysis run) | 86.2% | Not measured | Only Gemini 2.5 Pro measured |
| SimpleQA Verified | Not measured | 20.0% | Only Mistral Large 4 measured |
| LMArena Text: science | 1480 | 1448 | Gemini 2.5 Pro |
| LMArena Text: medicine and healthcare | 1476 | 1433 | Gemini 2.5 Pro |
| LMArena Text: legal and government | 1480 | 1425 | Gemini 2.5 Pro |
| LMArena Text: business and finance | 1439 | 1439 | Gemini 2.5 Pro |
| FACTS Benchmark Suite | 61.5% | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1167 | 1257 | Mistral Large 4 |
| Design Arena: UI components | 1137 | 1272 | Mistral Large 4 |
| Design Arena: game dev | 1111 | 1225 | Mistral Large 4 |
| Design Arena: data viz | 1222 | 1275 | Mistral Large 4 |
| Design Arena: 3D | 1080 | 1252 | Mistral Large 4 |
| Design Arena: all code categories | 1152 | 1259 | Mistral Large 4 |
| Design Arena: SVG | Not measured | 1232 | Only Mistral Large 4 measured |
| Design Arena: ASCII art | Not measured | 1202 | Only Mistral Large 4 measured |
| LiveBench design | Not measured | 65.6% | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index138
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.5% | Only Mistral Large 4 measured |
| SAGE (Vals AI) | 41.9% | Not measured | Only Gemini 2.5 Pro measured |
| MedScribe (Vals AI) | 73.5% | 80.4% | Mistral Large 4 |
| IFBench | 48.7% | Not measured | Only Gemini 2.5 Pro measured |
| Long context reasoning (AA-LCR) | 69.0% | 81.3% | Mistral Large 4 |
| DTBench | 82.4% | 88.2% | Mistral Large 4 |
| LMCA | 34.8% | 35.8% | Mistral Large 4 |
| Creative writing (Lech Mazur) | 83.8% | Not measured | Only Gemini 2.5 Pro measured |
| Surface Evolver Bench | Not measured | 28.1% | Only Mistral Large 4 measured |
| Furniture assembly | Not measured | 20.8% | Only Mistral Large 4 measured |
| LMArena Text | 1458 | 1431 | Gemini 2.5 Pro |
| LMArena Text: instruction following | 1437 | 1422 | Gemini 2.5 Pro |
| LMArena Text: creative writing | 1454 | 1363 | Gemini 2.5 Pro |
| LMArena Vision | 1263 | 1272 | Mistral Large 4 |
| LMArena Text: English | 1458 | 1433 | Gemini 2.5 Pro |
| LMArena Text: non-English | 1452 | 1422 | Gemini 2.5 Pro |
| LMArena Text: Chinese | 1507 | 1492 | Gemini 2.5 Pro |
| LMArena Text: German | 1487 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: Japanese | 1461 | 1415 | Gemini 2.5 Pro |
| LMArena Text: Korean | 1434 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: French | 1473 | 1492 | Mistral Large 4 |
| LMArena Text: Spanish | 1474 | 1455 | Gemini 2.5 Pro |
| LMArena Text: Russian | 1461 | 1417 | Gemini 2.5 Pro |
| LMArena Text: Polish | 1479 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Text: multi-turn | 1453 | 1435 | Gemini 2.5 Pro |
| LMArena Text: longer queries | 1449 | 1428 | Gemini 2.5 Pro |
| LMArena Text: writing and language | 1454 | 1386 | Gemini 2.5 Pro |
| LMArena Text: entertainment and media | 1441 | 1378 | Gemini 2.5 Pro |
| LMArena Vision: English | 1261 | 1283 | Mistral Large 4 |
| LMArena Vision: Chinese | 1300 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: reading text | 1270 | 1284 | Mistral Large 4 |
| LMArena Vision: humor | 1262 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: captioning | 1304 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: recognizing things | 1283 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Vision: creative writing | 1265 | Not measured | Only Gemini 2.5 Pro measured |
| LMArena Document | 1421 | Not measured | Only Gemini 2.5 Pro measured |
| Neither model has a result on the other 10 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 2.5 Pro | Mistral Large 4 | 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
Gemini 2.5 Pro$0.0063Fits in one request
Mistral Large 4$0.0034Fits in one request
Mistral Large 4 costs less
Repository review
50K input + 3K output tokens
Gemini 2.5 Pro$0.092Fits in one request
Mistral Large 4$0.081Fits in one request
Mistral Large 4 costs less
Agent loop
200K input + 10K output tokens
Gemini 2.5 Pro$0.350Fits in one request
Mistral Large 4$0.314Fits in one request
Mistral Large 4 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 | Google Gemini 2.5 Pro | Mistral Large 4 |
|---|---|---|
| Maker | Mistral AI | |
| Weights | No public weights listed | No public weights listed |
| Released | June 17, 2025 | October 6, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.25 | $1.36 |
| Output $/Mtok | $10.00 | $4.18 |
| Coding index | 19.1 | 56.4 |
| Independent measurements behind it | 3 | 5 |
| Cost per solved task | $0.64 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 2.5 Pro better than Mistral Large 4 for coding?
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 19.1 for Gemini 2.5 Pro. Pick Gemini 2.5 Pro for work measured by LMArena Text: hard prompts or LMArena Text: expert, where it leads.
Which is cheaper, Gemini 2.5 Pro or Mistral Large 4?
Gemini 2.5 Pro costs $1.25 per million input tokens and $10.00 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for Gemini 2.5 Pro only.
Which has the bigger context window, Gemini 2.5 Pro or Mistral Large 4?
Neither: both take 1.05M tokens.
How many benchmarks is the Gemini 2.5 Pro vs Mistral Large 4 comparison based on?
51 benchmarks have a result for both models as of October 22, 2026. Gemini 2.5 Pro's coding index rests on 3 independent benchmarks and Mistral Large 4's on 5. Where only one model has a result, the page says so instead of naming a winner.