Gemini 3.5 Flash vs Mistral Large 4
Mistral Large 4 leads Gemini 3.5 Flash on coding, 56.4 to 39.8 on the Vibe Coding Index, and Mistral Large 4 costs 2.2x less per output token ($4.18 vs $9.00 per million). Updated October 21, 2026; 66 benchmarks have a result for both.
vs boards won of 66 shared, 1 tied
Gemini 3.5 Flash or Mistral Large 4: which to pick
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash.
Pick Gemini 3.5 Flash for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Model AGemini 3.5 FlashGoogle39.8/1004 independent benchmarks$1.21 per solved taskModel BMistral Large 4Mistral AI56.4/1005 independent benchmarksNo cost per solved task
- Shared results
- 66
- Gemini 3.5 Flash only
- 46
- Mistral Large 4 only
- 15
- 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
Mistral Large 4
Mistral Large 4 scores 56.4 against 39.8.
4 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 33.6.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only Gemini 3.5 Flash has a GPQA Diamond result, 92.7%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.5 Flash has a MMLU Pro result, 89.5%.
Directional only
Web design
Design Arena: websites
Gemini 3.5 Flash
Gemini 3.5 Flash leads, 1268 against 1258.
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 3.5 Flash $0.0060, Mistral Large 4 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.5 Flash has the number, $1.21.
Directional only
At a glance
- Coding index
- Gemini 3.5 Flash 39.8 from 4 benchmarks, Mistral Large 4 56.4 from 5 benchmarks.
- Widest category
- Knowledge, 15.4 points apart on average over 6 shared benchmarks.
- Widest single gap
- SimpleQA Verified: Gemini 3.5 Flash 66.2% against Mistral Large 4 20.0%, 46.2 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash $9.00 against Mistral Large 4 $4.18 per million output tokens, 2.2x 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 3.5 Flash | Bars | Mistral Large 4 | Ties |
|---|---|---|---|---|
| Coding | 3 | 7 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 2 | 2 | ||
| Reasoning | 8 | 0 | ||
| Math | 4 | 1 | 1 tie | |
| Knowledge | 6 | 0 | ||
| Web design | 5 | 3 | ||
| General | 19 | 3 | ||
| All shared boards | 48 | 17 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index37
| Benchmark | Gemini 3.5 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 60.0% | Only Mistral Large 4 measured |
| LMArena WebDev | 1499 | 1543 | Mistral Large 4 |
| LiveCodeBench (Vals AI) | 87.6% | Not measured | Only Gemini 3.5 Flash measured |
| SWE-bench Verified (Vals AI) | 78.8% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 4 (Vals AI) | 6.1% | 27.8% | Mistral Large 4 |
| Vibe Code Bench (Vals AI) | 48.7% | 78.4% | Mistral Large 4 |
| Code migration (Vals AI) | 26.8% | 30.6% | Mistral Large 4 |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.5 Flash measured |
| IOI (Vals AI) | Not measured | 45.3% | Only Mistral Large 4 measured |
| Terminal-Bench 2.1 (Vals AI) | 74.2% | Not measured | Only Gemini 3.5 Flash 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 |
| SkillsBench (Vals AI) | 52.7% | Not measured | Only Gemini 3.5 Flash measured |
| SciCode | 53.9% | 54.2% | Mistral Large 4 |
| Terminal-Bench Hard (Artificial Analysis run) | 46.2% | Not measured | Only Gemini 3.5 Flash measured |
| FrontierCode | Not measured | 39.4% | Only Mistral Large 4 measured |
| WeirdML | 62.6% | Not measured | Only Gemini 3.5 Flash measured |
| ALE-Bench | 911.0 | 1213.2 | Mistral Large 4 |
| LMArena Text: coding | 1493 | 1478 | Gemini 3.5 Flash |
| LMArena Text: software and IT | 1494 | 1467 | Gemini 3.5 Flash |
| LMArena WebDev: React | 1495 | 1559 | Mistral Large 4 |
| LMArena WebDev: HTML | 1522 | 1487 | Gemini 3.5 Flash |
| LMArena WebDev: from an image | 1504 | Not measured | Only Gemini 3.5 Flash measured |
| SciCode | 12.3% | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Gemini 3.5 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 33.6 | 38.4 | Mistral Large 4 |
| Epoch Capabilities Index | 154.9 | 150.0 | Gemini 3.5 Flash |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index22
| Benchmark | Gemini 3.5 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1202 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building full-stack apps | 1197 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building mobile apps | 1174 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Android apps | 1184 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building Godot games | 1098 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: agents building games | 1180 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: HTML slides | 1142 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: PowerPoint slides | 1179 | Not measured | Only Gemini 3.5 Flash 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) | 57.9% | 54.7% | Gemini 3.5 Flash |
| Tax Agent Bench (Vals AI) | 21.6% | 30.4% | Mistral Large 4 |
| Legal Research Bench (Vals AI) | 30.8% | 31.7% | Mistral Large 4 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 17.5% | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | 63.5% | 56.2% | Gemini 3.5 Flash |
| BioMysteryBench (Vals AI) | Not measured | 67.0% | Only Mistral Large 4 measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only Gemini 3.5 Flash measured |
| τ²-Bench Telecom | 95.6% | Not measured | Only Gemini 3.5 Flash measured |
| APEX-Agents | 27.5% | Not measured | Only Gemini 3.5 Flash measured |
| Vending-Bench 2 | $5,396 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 20 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Gemini 3.5 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| GPQA Diamond | 92.7% | Not measured | Only Gemini 3.5 Flash measured |
| LiveBench reasoning | Not measured | 83.9% | Only Mistral Large 4 measured |
| MysteryMechanism (Vals AI) | Not measured | 12.2% | Only Mistral Large 4 measured |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only Gemini 3.5 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 92.2% | Not measured | Only Gemini 3.5 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 42.7% | 35.0% | Gemini 3.5 Flash |
| GPQA Diamond (Epoch AI run) | 92.8% | 88.1% | Gemini 3.5 Flash |
| ARC-AGI | 92.5% | Not measured | Only Gemini 3.5 Flash measured |
| ARC-AGI-2 | 72.1% | Not measured | Only Gemini 3.5 Flash measured |
| SimpleBench | 76.7% | Not measured | Only Gemini 3.5 Flash measured |
| Chess puzzles | 45.0% | 33.0% | Gemini 3.5 Flash |
| Mystery game puzzles | 32.0% | 17.0% | Gemini 3.5 Flash |
| EBR-bench | 4.8% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: hard prompts | 1488 | 1444 | Gemini 3.5 Flash |
| LMArena Text: expert | 1495 | 1444 | Gemini 3.5 Flash |
| LMArena Text: hard prompts in English | 1483 | 1442 | Gemini 3.5 Flash |
| LMArena Vision: diagrams | 1323 | 1288 | Gemini 3.5 Flash |
| LMArena Vision: homework | 1330 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index41
| Benchmark | Gemini 3.5 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 95.6% | 98.3% | Mistral Large 4 |
| FrontierMath, tiers 1 to 3 | 62.8% | 58.6% | Gemini 3.5 Flash |
| FrontierMath, tier 4 | 26.8% | 26.8% | Tie |
| ProofBench | 31.0% | 10.0% | Gemini 3.5 Flash |
| LMArena Text: math | 1504 | 1469 | Gemini 3.5 Flash |
| LMArena Text: mathematical work | 1495 | 1462 | Gemini 3.5 Flash |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 3.5 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| MMLU Pro | 89.5% | Not measured | Only Gemini 3.5 Flash measured |
| LegalBench (Vals AI) | 83.6% | Not measured | Only Gemini 3.5 Flash measured |
| CorpFin (Vals AI) | 64.7% | Not measured | Only Gemini 3.5 Flash measured |
| TaxEval (Vals AI) | 74.4% | Not measured | Only Gemini 3.5 Flash measured |
| MortgageTax (Vals AI) | 68.1% | Not measured | Only Gemini 3.5 Flash measured |
| MedCode (Vals AI) | 55.8% | 40.7% | Gemini 3.5 Flash |
| SimpleQA Verified | 66.2% | 20.0% | Gemini 3.5 Flash |
| LMArena Text: science | 1495 | 1448 | Gemini 3.5 Flash |
| LMArena Text: medicine and healthcare | 1483 | 1433 | Gemini 3.5 Flash |
| LMArena Text: legal and government | 1488 | 1425 | Gemini 3.5 Flash |
| LMArena Text: business and finance | 1467 | 1439 | Gemini 3.5 Flash |
| FACTS Benchmark Suite | 63.1% | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index53
| Benchmark | Gemini 3.5 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | 1258 | Gemini 3.5 Flash |
| Design Arena: UI components | 1273 | 1275 | Mistral Large 4 |
| Design Arena: game dev | 1263 | 1226 | Gemini 3.5 Flash |
| Design Arena: data viz | 1236 | 1274 | Mistral Large 4 |
| Design Arena: 3D | 1244 | 1253 | Mistral Large 4 |
| Design Arena: all code categories | 1266 | 1259 | Gemini 3.5 Flash |
| Design Arena: SVG | 1254 | 1233 | Gemini 3.5 Flash |
| Design Arena: ASCII art | 1254 | 1202 | Gemini 3.5 Flash |
| LiveBench design | Not measured | 65.6% | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index193
| Benchmark | Gemini 3.5 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.5% | Only Mistral Large 4 measured |
| Public Benefits Bench (Vals AI) | 59.5% | Not measured | Only Gemini 3.5 Flash measured |
| SAGE (Vals AI) | 49.9% | Not measured | Only Gemini 3.5 Flash measured |
| MedScribe (Vals AI) | 76.6% | 80.4% | Mistral Large 4 |
| Vals Multimodal Index | 62.9% | Not measured | Only Gemini 3.5 Flash measured |
| IFBench | 76.3% | Not measured | Only Gemini 3.5 Flash measured |
| Long context reasoning (AA-LCR) | 74.3% | 81.3% | Mistral Large 4 |
| DTBench | 94.7% | 88.2% | Gemini 3.5 Flash |
| LMCA | 47.1% | 35.8% | Gemini 3.5 Flash |
| Surface Evolver Bench | 58.1% | 28.1% | Gemini 3.5 Flash |
| Furniture assembly | Not measured | 20.8% | Only Mistral Large 4 measured |
| LMArena Text | 1482 | 1431 | Gemini 3.5 Flash |
| LMArena Text: instruction following | 1467 | 1422 | Gemini 3.5 Flash |
| LMArena Text: creative writing | 1470 | 1363 | Gemini 3.5 Flash |
| LMArena Vision | 1308 | 1272 | Gemini 3.5 Flash |
| LMArena Text: English | 1481 | 1433 | Gemini 3.5 Flash |
| LMArena Text: non-English | 1475 | 1422 | Gemini 3.5 Flash |
| LMArena Text: Chinese | 1527 | 1492 | Gemini 3.5 Flash |
| LMArena Text: German | 1494 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: Japanese | 1486 | 1415 | Gemini 3.5 Flash |
| LMArena Text: Korean | 1448 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: French | 1490 | 1492 | Mistral Large 4 |
| LMArena Text: Spanish | 1480 | 1455 | Gemini 3.5 Flash |
| LMArena Text: Russian | 1493 | 1417 | Gemini 3.5 Flash |
| LMArena Text: Polish | 1516 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: multi-turn | 1481 | 1435 | Gemini 3.5 Flash |
| LMArena Text: longer queries | 1483 | 1428 | Gemini 3.5 Flash |
| LMArena Text: writing and language | 1478 | 1386 | Gemini 3.5 Flash |
| LMArena Text: entertainment and media | 1459 | 1378 | Gemini 3.5 Flash |
| LMArena Vision: English | 1305 | 1283 | Gemini 3.5 Flash |
| LMArena Vision: Chinese | 1377 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: reading text | 1317 | 1284 | Gemini 3.5 Flash |
| LMArena Vision: humor | 1321 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Document | 1463 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash | 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 3.5 Flash$0.0060Fits in one request
Mistral Large 4$0.0034Fits in one request
Mistral Large 4 costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash$0.102Fits in one request
Mistral Large 4$0.081Fits in one request
Mistral Large 4 costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 Flash$0.390Fits 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 3.5 Flash | Mistral Large 4 |
|---|---|---|
| Maker | Mistral AI | |
| Weights | No public weights listed | No public weights listed |
| Released | May 19, 2026 | October 6, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.50 | $1.36 |
| Output $/Mtok | $9.00 | $4.18 |
| Coding index | 39.8 | 56.4 |
| Independent measurements behind it | 4 | 5 |
| Cost per solved task | $1.21 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash better than Mistral Large 4 for coding?
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 39.8 for Gemini 3.5 Flash. Pick Gemini 3.5 Flash for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.
Which is cheaper, Gemini 3.5 Flash or Mistral Large 4?
Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for Gemini 3.5 Flash only.
Which has the bigger context window, Gemini 3.5 Flash or Mistral Large 4?
Neither: both take 1.05M tokens.
How many benchmarks is the Gemini 3.5 Flash vs Mistral Large 4 comparison based on?
66 benchmarks have a result for both models as of October 21, 2026. Gemini 3.5 Flash's coding index rests on 4 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.