Gemini 3.7 Flash vs Mistral Medium 3.5
Gemini 3.7 Flash leads Mistral Medium 3.5 on coding, 58.0 to 25.5 on the Vibe Coding Index, and Gemini 3.7 Flash costs 2.0x less per output token ($3.75 vs $7.50 per million). Updated October 22, 2026; 72 benchmarks have a result for both.
Gemini 3.7 Flash or Mistral Medium 3.5: which to pick
Pick Gemini 3.7 Flash for coding: it scores 58.0 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5.
Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
- Shared results
- 72
- Gemini 3.7 Flash only
- 42
- Mistral Medium 3.5 only
- 9
- Like-for-like categories
- 8 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
Gemini 3.7 Flash
Gemini 3.7 Flash scores 58.0 against 25.5.
6 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 39.6 against 14.2.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Mistral Medium 3.5 has a AA Agentic Index result, 7.0.
Directional only
Reasoning
GPQA Diamond
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 93.9% against 34.9%.
Same board, both measured
Knowledge
MMLU Pro
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 90.1% against 75.3%.
Same board, both measured
Web design
Design Arena: websites
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 1303 against 1142.
Same board, both measured
Long documents
Listed context window
Gemini 3.7 Flash
Gemini 3.7 Flash takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Gemini 3.7 Flash
Gemini 3.7 Flash $0.0026, Mistral Medium 3.5 $0.0053 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Gemini 3.7 Flash
Gemini 3.7 Flash $1.78, Mistral Medium 3.5 $6.02.
Published attempt cost and pass rate
At a glance
- Coding index
- Gemini 3.7 Flash 58.0 from 6 benchmarks, Mistral Medium 3.5 25.5 from 3 benchmarks.
- Widest category
- Agentic work, 32.7 points apart on average over 4 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Gemini 3.7 Flash 70.4% against Mistral Medium 3.5 2.9%, 67.5 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.7 Flash $3.75 against Mistral Medium 3.5 $7.50 per million output tokens, 2.0x apart.
- Context window
- Gemini 3.7 Flash takes 1.05M tokens, Mistral Medium 3.5 262K.
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 3.7 Flash | Bars | Mistral Medium 3.5 | Ties |
|---|---|---|---|---|
| Coding | 12 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 4 | 0 | ||
| Reasoning | 8 | 0 | ||
| Math | 3 | 0 | ||
| Knowledge | 8 | 0 | ||
| Web design | 8 | 0 | ||
| General | 27 | 0 | ||
| All shared boards | 72 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index120
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| LiveBench coding | 80.5% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena WebDev | 1591 | 1264 | Gemini 3.7 Flash |
| AA Coding Index | 71.5 | 46.9 | Gemini 3.7 Flash |
| LiveCodeBench (Vals AI) | 88.7% | Not measured | Only Gemini 3.7 Flash measured |
| SWE-bench Verified (Vals AI) | 80.8% | 66.4% | Gemini 3.7 Flash |
| Terminal-Bench 4 (Vals AI) | 12.1% | Not measured | Only Gemini 3.7 Flash measured |
| Vibe Code Bench (Vals AI) | 70.4% | 2.9% | Gemini 3.7 Flash |
| Code migration (Vals AI) | 34.8% | 5.1% | Gemini 3.7 Flash |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.7 Flash measured |
| IOI (Vals AI) | 67.8% | Not measured | Only Gemini 3.7 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 77.5% | 39.0% | Gemini 3.7 Flash |
| SkillsBench (Vals AI) | 65.9% | Not measured | Only Gemini 3.7 Flash measured |
| CyberBench (Vals AI) | 43.8% | Not measured | Only Gemini 3.7 Flash measured |
| SciCode | 59.8% | 40.2% | Gemini 3.7 Flash |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 33.3% | Only Mistral Medium 3.5 measured |
| FrontierCode | 43.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierSWE | 20.3% | Not measured | Only Gemini 3.7 Flash measured |
| ALE-Bench | 904.3 | 764.0 | Gemini 3.7 Flash |
| LMArena Text: coding | 1499 | 1460 | Gemini 3.7 Flash |
| LMArena Text: software and IT | 1498 | 1458 | Gemini 3.7 Flash |
| LMArena WebDev: React | 1587 | 1254 | Gemini 3.7 Flash |
| LMArena WebDev: HTML | 1593 | 1308 | Gemini 3.7 Flash |
| LMArena WebDev: from an image | 1599 | Not measured | Only Gemini 3.7 Flash measured |
| SciCode | 13.8% | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 39.6 | 14.2 | Gemini 3.7 Flash |
| Epoch Capabilities Index | 158.0 | 141.4 | Gemini 3.7 Flash |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| AA Agentic Index | Not measured | 7.0 | Only Mistral Medium 3.5 measured |
| Design Arena: agents building web apps | 1223 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building full-stack apps | 1208 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building mobile apps | 1229 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | 1243 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Godot games | 1264 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: agents building games | 1235 | Not measured | Only Gemini 3.7 Flash measured |
| Design Arena: spreadsheets | 1058 | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench research | 76.5% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench browser | 56.0% | Not measured | Only Gemini 3.7 Flash measured |
| LiveBench long agentic | 28.3% | Not measured | Only Gemini 3.7 Flash measured |
| SREBench (Vals AI) | 4.6% | Not measured | Only Gemini 3.7 Flash measured |
| Finance Agent (Vals AI) | 59.0% | 32.1% | Gemini 3.7 Flash |
| Tax Agent Bench (Vals AI) | 22.8% | 4.5% | Gemini 3.7 Flash |
| Legal Research Bench (Vals AI) | 34.6% | 9.1% | Gemini 3.7 Flash |
| Excel Modeling Benchmark (Vals AI) | 71.3% | 11.2% | Gemini 3.7 Flash |
| Terminal-Bench-Science (Vals AI) | 7.1% | Not measured | Only Gemini 3.7 Flash measured |
| τ²-Bench Telecom | Not measured | 94.2% | Only Mistral Medium 3.5 measured |
| APEX-Agents | 67.8% | Not measured | Only Gemini 3.7 Flash measured |
| Remote Labor Index | 5.0% | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 21 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 93.9% | 34.9% | Gemini 3.7 Flash |
| LiveBench reasoning | 87.8% | Not measured | Only Gemini 3.7 Flash measured |
| MMMU Pro (Vals AI) | 89.0% | Not measured | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 94.5% | 74.8% | Gemini 3.7 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 47.9% | 13.8% | Gemini 3.7 Flash |
| GPQA Diamond (Epoch AI run) | 94.8% | Not measured | Only Gemini 3.7 Flash measured |
| ARC-AGI | 95.5% | Not measured | Only Gemini 3.7 Flash measured |
| ARC-AGI-2 | 84.6% | Not measured | Only Gemini 3.7 Flash measured |
| Chess puzzles | 66.0% | Not measured | Only Gemini 3.7 Flash measured |
| Mystery game puzzles | 37.0% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts | 1495 | 1436 | Gemini 3.7 Flash |
| LMArena Text: expert | 1512 | 1432 | Gemini 3.7 Flash |
| LMArena Text: hard prompts in English | 1487 | 1445 | Gemini 3.7 Flash |
| LMArena Vision: diagrams | 1329 | 1254 | Gemini 3.7 Flash |
| LMArena Vision: homework | 1320 | 1230 | Gemini 3.7 Flash |
| Kagi LLM Benchmark | Not measured | 41.4% | Only Mistral Medium 3.5 measured |
| Neither model has a result on the other 6 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 97.2% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | 71.6% | Not measured | Only Gemini 3.7 Flash measured |
| FrontierMath, tier 4 | 36.6% | Not measured | Only Gemini 3.7 Flash measured |
| ProofBench | 58.0% | 9.0% | Gemini 3.7 Flash |
| LMArena Text: math | 1511 | 1431 | Gemini 3.7 Flash |
| LMArena Text: mathematical work | 1502 | 1440 | Gemini 3.7 Flash |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| MMLU Pro | 90.1% | 75.3% | Gemini 3.7 Flash |
| LegalBench (Vals AI) | 87.3% | Not measured | Only Gemini 3.7 Flash measured |
| CaseLaw (Vals AI) | Not measured | 44.2% | Only Mistral Medium 3.5 measured |
| CorpFin (Vals AI) | Not measured | 58.8% | Only Mistral Medium 3.5 measured |
| TaxEval (Vals AI) | 74.7% | 68.0% | Gemini 3.7 Flash |
| MortgageTax (Vals AI) | 66.7% | 28.9% | Gemini 3.7 Flash |
| MedCode (Vals AI) | 53.4% | 33.8% | Gemini 3.7 Flash |
| SimpleQA Verified | 69.2% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: science | 1511 | 1428 | Gemini 3.7 Flash |
| LMArena Text: medicine and healthcare | 1494 | 1409 | Gemini 3.7 Flash |
| LMArena Text: legal and government | 1496 | 1437 | Gemini 3.7 Flash |
| LMArena Text: business and finance | 1479 | 1426 | Gemini 3.7 Flash |
| FACTS Benchmark Suite | 71.2% | Not measured | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1303 | 1142 | Gemini 3.7 Flash |
| Design Arena: UI components | 1296 | 1076 | Gemini 3.7 Flash |
| Design Arena: game dev | 1317 | 1079 | Gemini 3.7 Flash |
| Design Arena: data viz | 1315 | 1120 | Gemini 3.7 Flash |
| Design Arena: 3D | 1307 | 1060 | Gemini 3.7 Flash |
| Design Arena: all code categories | 1308 | 1121 | Gemini 3.7 Flash |
| Design Arena: SVG | 1283 | 949 | Gemini 3.7 Flash |
| Design Arena: ASCII art | 1276 | 1062 | Gemini 3.7 Flash |
| LiveBench design | 73.2% | Not measured | Only Gemini 3.7 Flash measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index270
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | Leader |
|---|---|---|---|
| LiveBench data analysis | 68.0% | Not measured | Only Gemini 3.7 Flash measured |
| SAGE (Vals AI) | 49.2% | 37.6% | Gemini 3.7 Flash |
| MedScribe (Vals AI) | 83.9% | 67.7% | Gemini 3.7 Flash |
| Vals Multimodal Index | Not measured | 34.8% | Only Mistral Medium 3.5 measured |
| IFBench | Not measured | 68.8% | Only Mistral Medium 3.5 measured |
| Long context reasoning (AA-LCR) | 83.0% | 69.3% | Gemini 3.7 Flash |
| DTBench | 96.8% | 75.5% | Gemini 3.7 Flash |
| LMCA | 50.4% | 26.1% | Gemini 3.7 Flash |
| Surface Evolver Bench | Not measured | 26.9% | Only Mistral Medium 3.5 measured |
| Furniture assembly | 26.7% | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text | 1489 | 1421 | Gemini 3.7 Flash |
| LMArena Text: instruction following | 1484 | 1415 | Gemini 3.7 Flash |
| LMArena Text: creative writing | 1488 | 1374 | Gemini 3.7 Flash |
| LMArena Vision | 1314 | 1222 | Gemini 3.7 Flash |
| LMArena Text: English | 1483 | 1433 | Gemini 3.7 Flash |
| LMArena Text: non-English | 1487 | 1404 | Gemini 3.7 Flash |
| LMArena Text: Chinese | 1552 | 1444 | Gemini 3.7 Flash |
| LMArena Text: German | 1506 | 1453 | Gemini 3.7 Flash |
| LMArena Text: Japanese | 1511 | Not measured | Only Gemini 3.7 Flash measured |
| LMArena Text: Korean | 1481 | 1384 | Gemini 3.7 Flash |
| LMArena Text: French | 1500 | 1448 | Gemini 3.7 Flash |
| LMArena Text: Spanish | 1495 | 1411 | Gemini 3.7 Flash |
| LMArena Text: Russian | 1515 | 1395 | Gemini 3.7 Flash |
| LMArena Text: Polish | 1503 | 1430 | Gemini 3.7 Flash |
| LMArena Text: multi-turn | 1485 | 1423 | Gemini 3.7 Flash |
| LMArena Text: longer queries | 1492 | 1415 | Gemini 3.7 Flash |
| LMArena Text: writing and language | 1491 | 1384 | Gemini 3.7 Flash |
| LMArena Text: entertainment and media | 1477 | 1382 | Gemini 3.7 Flash |
| LMArena Vision: English | 1309 | 1240 | Gemini 3.7 Flash |
| LMArena Vision: Chinese | 1394 | 1244 | Gemini 3.7 Flash |
| LMArena Vision: reading text | 1322 | 1233 | Gemini 3.7 Flash |
| LMArena Vision: humor | 1299 | 1216 | Gemini 3.7 Flash |
| LMArena Vision: creative writing | 1312 | 1198 | Gemini 3.7 Flash |
| Neither model has a result on the other 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.7 Flash | Mistral Medium 3.5 | 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 3.7 Flash costs less
Repository review
50K input + 3K output tokens
Gemini 3.7 Flash costs less
Agent loop
200K input + 10K output tokens
Gemini 3.7 Flash 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 3.7 Flash | Mistral Medium 3.5 |
|---|---|---|
| Maker | Mistral AI | |
| Weights | No public weights listed | No public weights listed |
| Released | August 13, 2026 | April 30, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $0.75 | $1.50 |
| Output $/Mtok | $3.75 | $7.50 |
| Coding index | 58.0 | 25.5 |
| Independent measurements behind it | 6 | 3 |
| Cost per solved task | $1.78 | $6.02 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.7 Flash better than Mistral Medium 3.5 for coding?
Pick Gemini 3.7 Flash for coding: it scores 58.0 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5. Mistral Medium 3.5 is neither cheaper nor larger in context, and leads no benchmark both models were measured on.
Which is cheaper, Gemini 3.7 Flash or Mistral Medium 3.5?
Gemini 3.7 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Per solved SWE-bench Verified task, Gemini 3.7 Flash costs $1.78 and Mistral Medium 3.5 $6.02.
Which has the bigger context window, Gemini 3.7 Flash or Mistral Medium 3.5?
Gemini 3.7 Flash, with 1.05M tokens against 262K.
How many benchmarks is the Gemini 3.7 Flash vs Mistral Medium 3.5 comparison based on?
72 benchmarks have a result for both models as of October 22, 2026. Gemini 3.7 Flash's coding index rests on 6 independent benchmarks and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.