Codestral 2508 vs Gemini 3.7 Flash
Codestral 2508 costs 4.2x less per output token than Gemini 3.7 Flash ($0.90 vs $3.75 per million). Updated October 21, 2026; 7 benchmarks have a result for both.
vs boards won of 7 shared
Codestral 2508 or Gemini 3.7 Flash: which to pick
Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; Codestral 2508 has none, so the two cannot be ranked on coding.
Pick Codestral 2508 for output tokens 4.2x cheaper ($0.90 vs $3.75 per million).
Model ACodestral 2508Mistral AINot benchmarkedNo coding benchmarkNo cost per solved taskModel BGemini 3.7 FlashGoogle58.0/1006 independent benchmarks$1.78 per solved task
- Shared results
- 7
- Codestral 2508 only
- 1
- Gemini 3.7 Flash only
- 107
- Like-for-like categories
- 2 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 3.7 Flash has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Gemini 3.7 Flash has a AA Intelligence Index result, 39.6.
Directional only
Reasoning
GPQA Diamond
No call
Only Gemini 3.7 Flash has a GPQA Diamond result, 93.9%.
Directional only
Knowledge
MMLU Pro
No call
Only Gemini 3.7 Flash has a MMLU Pro result, 90.1%.
Directional only
Web design
Design Arena: websites
Gemini 3.7 Flash
Gemini 3.7 Flash leads, 1304 against 1013.
Same board, both measured
Long documents
Listed context window
Gemini 3.7 Flash
Gemini 3.7 Flash takes 1.05M tokens against 256K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Codestral 2508
Codestral 2508 $0.0008, Gemini 3.7 Flash $0.0026 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Gemini 3.7 Flash has the number, $1.78.
Directional only
At a glance
- Coding index
- Codestral 2508 not benchmarked, Gemini 3.7 Flash 58.0 from 6 benchmarks.
- Widest category
- Web design, 37.7 points apart on average over 6 shared benchmarks.
- Widest single gap
- Design Arena: game dev: Codestral 2508 968 against Gemini 3.7 Flash 1318, 43.8 points apart on a 0 to 100 scale.
- Output price
- Codestral 2508 $0.90 against Gemini 3.7 Flash $3.75 per million output tokens, 4.2x apart.
- Context window
- Codestral 2508 takes 256K tokens, Gemini 3.7 Flash 1.05M.
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 | Codestral 2508 | Bars | Gemini 3.7 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Web design | 0 | 6 | ||
| All shared boards | 0 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Codestral 2508 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 80.5% | Only Gemini 3.7 Flash measured |
| LMArena WebDev | Not measured | 1591 | Only Gemini 3.7 Flash measured |
| AA Coding Index | Not measured | 71.5 | Only Gemini 3.7 Flash measured |
| LiveCodeBench (Vals AI) | Not measured | 88.7% | Only Gemini 3.7 Flash measured |
| SWE-bench Verified (Vals AI) | Not measured | 80.8% | Only Gemini 3.7 Flash measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 12.1% | Only Gemini 3.7 Flash measured |
| Vibe Code Bench (Vals AI) | Not measured | 70.4% | Only Gemini 3.7 Flash measured |
| Code migration (Vals AI) | Not measured | 34.8% | Only Gemini 3.7 Flash measured |
| ProgramBench (Vals AI) | Not measured | 0.0% | Only Gemini 3.7 Flash measured |
| IOI (Vals AI) | Not measured | 67.8% | Only Gemini 3.7 Flash measured |
| Terminal-Bench 2.1 (Vals AI) | Not measured | 77.5% | Only Gemini 3.7 Flash measured |
| SkillsBench (Vals AI) | Not measured | 65.9% | Only Gemini 3.7 Flash measured |
| CyberBench (Vals AI) | Not measured | 43.8% | Only Gemini 3.7 Flash measured |
| SciCode | Not measured | 59.8% | Only Gemini 3.7 Flash measured |
| FrontierCode | Not measured | 43.6% | Only Gemini 3.7 Flash measured |
| FrontierSWE | Not measured | 20.3% | Only Gemini 3.7 Flash measured |
| ALE-Bench | 137.8 | 904.3 | Gemini 3.7 Flash |
| LMArena Text: coding | Not measured | 1499 | Only Gemini 3.7 Flash measured |
| LMArena Text: software and IT | Not measured | 1498 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: React | Not measured | 1587 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: HTML | Not measured | 1593 | Only Gemini 3.7 Flash measured |
| LMArena WebDev: from an image | Not measured | 1599 | Only Gemini 3.7 Flash measured |
| SciCode | Not measured | 13.8% | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Codestral 2508 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | Not measured | 39.6 | Only Gemini 3.7 Flash measured |
| Epoch Capabilities Index | Not measured | 158.0 | Only Gemini 3.7 Flash measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
| Benchmark | Codestral 2508 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | Not measured | 1223 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building full-stack apps | Not measured | 1208 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building mobile apps | Not measured | 1230 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Android apps | Not measured | 1242 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building Godot games | Not measured | 1264 | Only Gemini 3.7 Flash measured |
| Design Arena: agents building games | Not measured | 1235 | Only Gemini 3.7 Flash measured |
| Design Arena: spreadsheets | Not measured | 1053 | Only Gemini 3.7 Flash measured |
| LiveBench research | Not measured | 76.5% | Only Gemini 3.7 Flash measured |
| LiveBench browser | Not measured | 56.0% | Only Gemini 3.7 Flash measured |
| LiveBench long agentic | Not measured | 28.3% | Only Gemini 3.7 Flash measured |
| SREBench (Vals AI) | Not measured | 4.6% | Only Gemini 3.7 Flash measured |
| Finance Agent (Vals AI) | Not measured | 59.0% | Only Gemini 3.7 Flash measured |
| Tax Agent Bench (Vals AI) | Not measured | 22.8% | Only Gemini 3.7 Flash measured |
| Legal Research Bench (Vals AI) | Not measured | 34.6% | Only Gemini 3.7 Flash measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 71.3% | Only Gemini 3.7 Flash measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 7.1% | Only Gemini 3.7 Flash measured |
| APEX-Agents | Not measured | 67.8% | Only Gemini 3.7 Flash measured |
| Remote Labor Index | Not measured | 5.0% | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 23 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
| Benchmark | Codestral 2508 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| GPQA Diamond | Not measured | 93.9% | Only Gemini 3.7 Flash measured |
| LiveBench reasoning | Not measured | 87.8% | Only Gemini 3.7 Flash measured |
| MMMU Pro (Vals AI) | Not measured | 89.0% | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 94.5% | Only Gemini 3.7 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 47.9% | Only Gemini 3.7 Flash measured |
| GPQA Diamond (Epoch AI run) | Not measured | 94.8% | Only Gemini 3.7 Flash measured |
| ARC-AGI | Not measured | 95.5% | Only Gemini 3.7 Flash measured |
| ARC-AGI-2 | Not measured | 84.6% | Only Gemini 3.7 Flash measured |
| Chess puzzles | Not measured | 66.0% | Only Gemini 3.7 Flash measured |
| Mystery game puzzles | Not measured | 37.0% | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts | Not measured | 1495 | Only Gemini 3.7 Flash measured |
| LMArena Text: expert | Not measured | 1512 | Only Gemini 3.7 Flash measured |
| LMArena Text: hard prompts in English | Not measured | 1487 | Only Gemini 3.7 Flash measured |
| LMArena Vision: diagrams | Not measured | 1329 | Only Gemini 3.7 Flash measured |
| LMArena Vision: homework | Not measured | 1320 | Only Gemini 3.7 Flash measured |
| Kagi LLM Benchmark | 32.5% | Not measured | Only Codestral 2508 measured |
| Neither model has a result on the other 6 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Codestral 2508 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 97.2% | Only Gemini 3.7 Flash measured |
| FrontierMath, tiers 1 to 3 | Not measured | 71.6% | Only Gemini 3.7 Flash measured |
| FrontierMath, tier 4 | Not measured | 36.6% | Only Gemini 3.7 Flash measured |
| ProofBench | Not measured | 58.0% | Only Gemini 3.7 Flash measured |
| LMArena Text: math | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: mathematical work | Not measured | 1502 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards, none shared
| Benchmark | Codestral 2508 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| MMLU Pro | Not measured | 90.1% | Only Gemini 3.7 Flash measured |
| LegalBench (Vals AI) | Not measured | 87.3% | Only Gemini 3.7 Flash measured |
| TaxEval (Vals AI) | Not measured | 74.7% | Only Gemini 3.7 Flash measured |
| MortgageTax (Vals AI) | Not measured | 66.7% | Only Gemini 3.7 Flash measured |
| MedCode (Vals AI) | Not measured | 53.4% | Only Gemini 3.7 Flash measured |
| SimpleQA Verified | Not measured | 69.2% | Only Gemini 3.7 Flash measured |
| LMArena Text: science | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: medicine and healthcare | Not measured | 1494 | Only Gemini 3.7 Flash measured |
| LMArena Text: legal and government | Not measured | 1496 | Only Gemini 3.7 Flash measured |
| LMArena Text: business and finance | Not measured | 1479 | Only Gemini 3.7 Flash measured |
| FACTS Benchmark Suite | Not measured | 71.2% | Only Gemini 3.7 Flash 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 | Codestral 2508 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1013 | 1304 | Gemini 3.7 Flash |
| Design Arena: UI components | 1017 | 1299 | Gemini 3.7 Flash |
| Design Arena: game dev | 968 | 1318 | Gemini 3.7 Flash |
| Design Arena: data viz | 1017 | 1315 | Gemini 3.7 Flash |
| Design Arena: 3D | 1020 | 1308 | Gemini 3.7 Flash |
| Design Arena: all code categories | 1007 | 1308 | Gemini 3.7 Flash |
| Design Arena: SVG | Not measured | 1283 | Only Gemini 3.7 Flash measured |
| Design Arena: ASCII art | Not measured | 1276 | Only Gemini 3.7 Flash measured |
| LiveBench design | Not measured | 73.2% | Only Gemini 3.7 Flash measured |
GeneralDirectional onlyPublic boards, shown as published, kept out of the index30 boards, none shared
| Benchmark | Codestral 2508 | Gemini 3.7 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 68.0% | Only Gemini 3.7 Flash measured |
| SAGE (Vals AI) | Not measured | 49.2% | Only Gemini 3.7 Flash measured |
| MedScribe (Vals AI) | Not measured | 83.9% | Only Gemini 3.7 Flash measured |
| Long context reasoning (AA-LCR) | Not measured | 83.0% | Only Gemini 3.7 Flash measured |
| DTBench | Not measured | 96.8% | Only Gemini 3.7 Flash measured |
| LMCA | Not measured | 50.4% | Only Gemini 3.7 Flash measured |
| Furniture assembly | Not measured | 26.7% | Only Gemini 3.7 Flash measured |
| LMArena Text | Not measured | 1489 | Only Gemini 3.7 Flash measured |
| LMArena Text: instruction following | Not measured | 1484 | Only Gemini 3.7 Flash measured |
| LMArena Text: creative writing | Not measured | 1488 | Only Gemini 3.7 Flash measured |
| LMArena Vision | Not measured | 1314 | Only Gemini 3.7 Flash measured |
| LMArena Text: English | Not measured | 1483 | Only Gemini 3.7 Flash measured |
| LMArena Text: non-English | Not measured | 1487 | Only Gemini 3.7 Flash measured |
| LMArena Text: Chinese | Not measured | 1552 | Only Gemini 3.7 Flash measured |
| LMArena Text: German | Not measured | 1506 | Only Gemini 3.7 Flash measured |
| LMArena Text: Japanese | Not measured | 1511 | Only Gemini 3.7 Flash measured |
| LMArena Text: Korean | Not measured | 1481 | Only Gemini 3.7 Flash measured |
| LMArena Text: French | Not measured | 1500 | Only Gemini 3.7 Flash measured |
| LMArena Text: Spanish | Not measured | 1495 | Only Gemini 3.7 Flash measured |
| LMArena Text: Russian | Not measured | 1515 | Only Gemini 3.7 Flash measured |
| LMArena Text: Polish | Not measured | 1503 | Only Gemini 3.7 Flash measured |
| LMArena Text: multi-turn | Not measured | 1485 | Only Gemini 3.7 Flash measured |
| LMArena Text: longer queries | Not measured | 1492 | Only Gemini 3.7 Flash measured |
| LMArena Text: writing and language | Not measured | 1491 | Only Gemini 3.7 Flash measured |
| LMArena Text: entertainment and media | Not measured | 1477 | Only Gemini 3.7 Flash measured |
| LMArena Vision: English | Not measured | 1309 | Only Gemini 3.7 Flash measured |
| LMArena Vision: Chinese | Not measured | 1394 | Only Gemini 3.7 Flash measured |
| LMArena Vision: reading text | Not measured | 1322 | Only Gemini 3.7 Flash measured |
| LMArena Vision: humor | Not measured | 1299 | Only Gemini 3.7 Flash measured |
| LMArena Vision: creative writing | Not measured | 1312 | Only Gemini 3.7 Flash measured |
| Neither model has a result on the other 16 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Codestral 2508 | Gemini 3.7 Flash | 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
Codestral 2508$0.0008Fits in one request
Gemini 3.7 Flash$0.0026Fits in one request
Codestral 2508 costs less
Repository review
50K input + 3K output tokens
Codestral 2508$0.018Fits in one request
Gemini 3.7 Flash$0.049Fits in one request
Codestral 2508 costs less
Agent loop
200K input + 10K output tokens
Codestral 2508$0.069Fits in one request
Gemini 3.7 Flash$0.188Fits in one request
Codestral 2508 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 | Mistral Codestral 2508 | Google Gemini 3.7 Flash |
|---|---|---|
| Maker | Mistral AI | |
| Weights | No public weights listed | No public weights listed |
| Released | August 1, 2025 | August 13, 2026 |
| Context window | 256K | 1.05M |
| Input $/Mtok | $0.30 | $0.75 |
| Output $/Mtok | $0.90 | $3.75 |
| Coding index | Not benchmarked | 58.0 |
| Independent measurements behind it | 0 | 6 |
| Cost per solved task | Not computable | $1.78 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Codestral 2508 better than Gemini 3.7 Flash for coding?
Only Gemini 3.7 Flash has a coding score, 58.0 on the Vibe Coding Index; Codestral 2508 has none, so the two cannot be ranked on coding. Pick Codestral 2508 for output tokens 4.2x cheaper ($0.90 vs $3.75 per million).
Which is cheaper, Codestral 2508 or Gemini 3.7 Flash?
Codestral 2508 costs $0.30 per million input tokens and $0.90 per million output tokens; Gemini 3.7 Flash costs $0.75 and $3.75. Cost per solved task is known for Gemini 3.7 Flash only.
Which has the bigger context window, Codestral 2508 or Gemini 3.7 Flash?
Gemini 3.7 Flash, with 1.05M tokens against 256K.
How many benchmarks is the Codestral 2508 vs Gemini 3.7 Flash comparison based on?
7 benchmarks have a result for both models as of October 21, 2026. Codestral 2508's coding index rests on 0 independent benchmarks and Gemini 3.7 Flash's on 6. Where only one model has a result, the page says so instead of naming a winner.