Gemini 3.5 Flash vs Mistral Large
Gemini 3.5 Flash leads Mistral Large on the Artificial Analysis Intelligence Index, 33.6 to 5.8, and Mistral Large costs 1.5x less per output token ($6.00 vs $9.00 per million). Updated October 21, 2026; 37 benchmarks have a result for both.
Gemini 3.5 Flash or Mistral Large: which to pick
Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding.
Pick Mistral Large for output tokens 1.5x cheaper ($6.00 vs $9.00 per million).
- Shared results
- 37
- Gemini 3.5 Flash only
- 73
- Mistral Large only
- 7
- Like-for-like categories
- 6 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 Gemini 3.5 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
Gemini 3.5 Flash
Gemini 3.5 Flash leads, 33.6 against 5.8.
Same board, both measured
Reasoning
GPQA Diamond
Gemini 3.5 Flash
Gemini 3.5 Flash leads, 92.7% against 47.7%.
Same board, both measured
Math
AIME
No call
Only Mistral Large has a AIME result, 9.2%.
Directional only
Knowledge
MMLU Pro
Gemini 3.5 Flash
Gemini 3.5 Flash leads, 89.5% against 69.7%.
Same board, both measured
Web design
Design Arena: websites
No call
Only Gemini 3.5 Flash has a Design Arena: websites result, 1268.
Directional only
Long documents
Listed context window
Gemini 3.5 Flash
Gemini 3.5 Flash takes 1.05M tokens against 128K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Mistral Large
Gemini 3.5 Flash $0.0060, Mistral Large $0.0050 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 not benchmarked.
- Widest category
- Reasoning, 43.9 points apart on average over 6 shared benchmarks.
- Widest single gap
- LMArena Text: Polish: Gemini 3.5 Flash 1516 against Mistral Large 1157, 59.9 points apart on a 0 to 100 scale.
- Output price
- Gemini 3.5 Flash $9.00 against Mistral Large $6.00 per million output tokens, 1.5x apart.
- Context window
- Gemini 3.5 Flash takes 1.05M tokens, Mistral Large 128K.
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 | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Intelligence | 2 | 0 | ||
| Reasoning | 6 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 6 | 0 | ||
| General | 18 | 0 | ||
| All shared boards | 37 | 0 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
| Benchmark | Gemini 3.5 Flash | Mistral Large | Leader |
|---|---|---|---|
| LMArena WebDev | 1499 | Not measured | Only Gemini 3.5 Flash measured |
| LiveCodeBench (Vals AI) | 87.6% | 37.1% | Gemini 3.5 Flash |
| SWE-bench Verified (Vals AI) | 78.8% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 4 (Vals AI) | 6.1% | Not measured | Only Gemini 3.5 Flash measured |
| Vibe Code Bench (Vals AI) | 48.7% | Not measured | Only Gemini 3.5 Flash measured |
| Code migration (Vals AI) | 26.8% | Not measured | Only Gemini 3.5 Flash measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | 74.2% | Not measured | Only Gemini 3.5 Flash measured |
| SkillsBench (Vals AI) | 52.7% | Not measured | Only Gemini 3.5 Flash measured |
| LiveCodeBench (Artificial Analysis run) | Not measured | 17.8% | Only Mistral Large measured |
| SciCode | 53.9% | Not measured | Only Gemini 3.5 Flash measured |
| Terminal-Bench Hard (Artificial Analysis run) | 46.2% | Not measured | Only Gemini 3.5 Flash measured |
| WeirdML | 62.6% | Not measured | Only Gemini 3.5 Flash measured |
| ALE-Bench | 911.0 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: coding | 1493 | 1275 | Gemini 3.5 Flash |
| LMArena Text: software and IT | 1494 | 1274 | Gemini 3.5 Flash |
| LMArena WebDev: React | 1495 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena WebDev: HTML | 1522 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena WebDev: from an image | 1504 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 3.5 Flash | Mistral Large | Leader |
|---|---|---|---|
| AA Intelligence Index | 33.6 | 5.8 | Gemini 3.5 Flash |
| Epoch Capabilities Index | 154.9 | 122.1 | Gemini 3.5 Flash |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | Gemini 3.5 Flash | Mistral Large | 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 |
| Finance Agent (Vals AI) | 57.9% | Not measured | Only Gemini 3.5 Flash measured |
| Tax Agent Bench (Vals AI) | 21.6% | Not measured | Only Gemini 3.5 Flash measured |
| Legal Research Bench (Vals AI) | 30.8% | Not measured | Only Gemini 3.5 Flash measured |
| Excel Modeling Benchmark (Vals AI) | 63.5% | Not measured | Only Gemini 3.5 Flash 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 23 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 3.5 Flash | Mistral Large | Leader |
|---|---|---|---|
| GPQA Diamond | 92.7% | 47.7% | Gemini 3.5 Flash |
| MMMU Pro (Vals AI) | 88.3% | Not measured | Only Gemini 3.5 Flash measured |
| GPQA Diamond (Artificial Analysis run) | 92.2% | 35.1% | Gemini 3.5 Flash |
| Humanity's Last Exam (Artificial Analysis run) | 42.7% | 3.5% | Gemini 3.5 Flash |
| GPQA Diamond (Epoch AI run) | 92.8% | Not measured | Only Gemini 3.5 Flash measured |
| 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% | Not measured | Only Gemini 3.5 Flash measured |
| Mystery game puzzles | 32.0% | Not measured | Only Gemini 3.5 Flash measured |
| EBR-bench | 4.8% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: hard prompts | 1488 | 1257 | Gemini 3.5 Flash |
| LMArena Text: expert | 1495 | 1208 | Gemini 3.5 Flash |
| LMArena Text: hard prompts in English | 1483 | 1268 | Gemini 3.5 Flash |
| LMArena Vision: diagrams | 1323 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: homework | 1330 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Gemini 3.5 Flash | Mistral Large | Leader |
|---|---|---|---|
| AIME | Not measured | 9.2% | Only Mistral Large measured |
| MATH 500 (Vals AI) | Not measured | 74.4% | Only Mistral Large measured |
| MGSM (Vals AI) | Not measured | 87.2% | Only Mistral Large measured |
| OTIS Mock AIME | 95.6% | Not measured | Only Gemini 3.5 Flash measured |
| FrontierMath, tiers 1 to 3 | 62.8% | Not measured | Only Gemini 3.5 Flash measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only Gemini 3.5 Flash measured |
| ProofBench | 31.0% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: math | 1504 | 1261 | Gemini 3.5 Flash |
| LMArena Text: mathematical work | 1495 | 1257 | Gemini 3.5 Flash |
| Neither model has a result on the other 4 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index60
| Benchmark | Gemini 3.5 Flash | Mistral Large | Leader |
|---|---|---|---|
| MMLU Pro | 89.5% | 69.7% | Gemini 3.5 Flash |
| 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% | 63.8% | Gemini 3.5 Flash |
| MortgageTax (Vals AI) | 68.1% | Not measured | Only Gemini 3.5 Flash measured |
| MedQA (Vals AI) | Not measured | 76.2% | Only Mistral Large measured |
| MedCode (Vals AI) | 55.8% | Not measured | Only Gemini 3.5 Flash measured |
| MMLU Pro (Artificial Analysis run) | Not measured | 51.5% | Only Mistral Large measured |
| SimpleQA Verified | 66.2% | Not measured | Only Gemini 3.5 Flash measured |
| MMLU | Not measured | 68.8% | Only Mistral Large measured |
| LMArena Text: science | 1495 | 1260 | Gemini 3.5 Flash |
| LMArena Text: medicine and healthcare | 1483 | 1255 | Gemini 3.5 Flash |
| LMArena Text: legal and government | 1488 | 1275 | Gemini 3.5 Flash |
| LMArena Text: business and finance | 1467 | 1238 | Gemini 3.5 Flash |
| Neither model has a result on the other 3 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
| Benchmark | Gemini 3.5 Flash | Mistral Large | Leader |
|---|---|---|---|
| Design Arena: websites | 1268 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: UI components | 1273 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: game dev | 1263 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: data viz | 1236 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: 3D | 1244 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: all code categories | 1266 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: SVG | 1254 | Not measured | Only Gemini 3.5 Flash measured |
| Design Arena: ASCII art | 1254 | Not measured | Only Gemini 3.5 Flash measured |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
| Benchmark | Gemini 3.5 Flash | Mistral Large | Leader |
|---|---|---|---|
| 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% | Not measured | Only Gemini 3.5 Flash measured |
| 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% | Not measured | Only Gemini 3.5 Flash measured |
| DTBench | 94.7% | 60.8% | Gemini 3.5 Flash |
| LMCA | 47.1% | Not measured | Only Gemini 3.5 Flash measured |
| Surface Evolver Bench | 58.1% | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text | 1482 | 1265 | Gemini 3.5 Flash |
| LMArena Text: instruction following | 1467 | 1249 | Gemini 3.5 Flash |
| LMArena Text: creative writing | 1470 | 1242 | Gemini 3.5 Flash |
| LMArena Vision | 1308 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Text: English | 1481 | 1284 | Gemini 3.5 Flash |
| LMArena Text: non-English | 1475 | 1235 | Gemini 3.5 Flash |
| LMArena Text: Chinese | 1527 | 1239 | Gemini 3.5 Flash |
| LMArena Text: German | 1494 | 1242 | Gemini 3.5 Flash |
| LMArena Text: Japanese | 1486 | 1170 | Gemini 3.5 Flash |
| LMArena Text: Korean | 1448 | 1202 | Gemini 3.5 Flash |
| LMArena Text: French | 1490 | 1325 | Gemini 3.5 Flash |
| LMArena Text: Spanish | 1480 | 1268 | Gemini 3.5 Flash |
| LMArena Text: Russian | 1493 | 1252 | Gemini 3.5 Flash |
| LMArena Text: Polish | 1516 | 1157 | Gemini 3.5 Flash |
| LMArena Text: multi-turn | 1481 | 1260 | Gemini 3.5 Flash |
| LMArena Text: longer queries | 1483 | 1261 | Gemini 3.5 Flash |
| LMArena Text: writing and language | 1478 | 1261 | Gemini 3.5 Flash |
| LMArena Text: entertainment and media | 1459 | 1230 | Gemini 3.5 Flash |
| LMArena Vision: English | 1305 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: Chinese | 1377 | Not measured | Only Gemini 3.5 Flash measured |
| LMArena Vision: reading text | 1317 | Not measured | Only Gemini 3.5 Flash measured |
| 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 13 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Gemini 3.5 Flash | Mistral Large | 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
Mistral Large costs less
Repository review
50K input + 3K output tokens
Gemini 3.5 Flash costs less
Agent loop
200K input + 10K output tokens
Gemini 3.5 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 3.5 Flash | Mistral Large |
|---|---|---|
| Maker | Mistral AI | |
| Weights | No public weights listed | No public weights listed |
| Released | May 19, 2026 | February 26, 2024 |
| Context window | 1.05M | 128K |
| Input $/Mtok | $1.50 | $2.00 |
| Output $/Mtok | $9.00 | $6.00 |
| Coding index | 39.8 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $1.21 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Gemini 3.5 Flash better than Mistral Large for coding?
Only Gemini 3.5 Flash has a coding score, 39.8 on the Vibe Coding Index; Mistral Large has none, so the two cannot be ranked on coding. Pick Mistral Large for output tokens 1.5x cheaper ($6.00 vs $9.00 per million).
Which is cheaper, Gemini 3.5 Flash or Mistral Large?
Gemini 3.5 Flash costs $1.50 per million input tokens and $9.00 per million output tokens; Mistral Large costs $2.00 and $6.00. 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?
Gemini 3.5 Flash, with 1.05M tokens against 128K.
How many benchmarks is the Gemini 3.5 Flash vs Mistral Large comparison based on?
37 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's on 0. Where only one model has a result, the page says so instead of naming a winner.