Mistral Large 4 vs Qwen3.8 Flash
Updated October 21, 2026. 7 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Qwen3.8 Flash for coding: it scores 87.4 on the Vibe Coding Index against 55.3 for Mistral Large 4, though on 1 benchmark against 2.
Pick Mistral Large 4 when the context window is larger, 1.05M against 1M tokens, or when the benchmark that matters is LiveBench data analysis, where it leads.
- Shared results
- 7
- Mistral Large 4 only
- 74
- Qwen3.8 Flash only
- 0
- Like-for-like categories
- 5 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Qwen3.8 Flash
Qwen3.8 Flash scores 87.4 against 55.3.
2 and 1 benchmarks behind the scores
Intelligence
AA Intelligence Index
No call
Only Mistral Large 4 has a AA Intelligence Index result, 38.4.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Large 4 has a Design Arena: websites result, 1258.
Directional only
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Qwen3.8 Flash
Mistral Large 4 $0.0034, Qwen3.8 Flash $0.0004 per turn.
List prices
At a glance
- Coding index
- Mistral Large 4 55.3 from 2 benchmarks, Qwen3.8 Flash 87.4 from 1 benchmark.
- Widest category
- Agentic work, 37.3 points apart on average over 3 shared benchmarks.
- Widest single gap
- LiveBench research: Mistral Large 4 28.1% against Qwen3.8 Flash 74.6%, 46.5 points apart on a 0 to 100 scale.
- Output price
- Mistral Large 4 $4.18 against Qwen3.8 Flash $0.47 per million output tokens, 8.9x apart.
- Context window
- Mistral Large 4 takes 1.05M tokens, Qwen3.8 Flash 1M.
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 | Mistral Large 4 | Bars | Qwen3.8 Flash | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 0 | 1 | ||
| Web design | 0 | 1 | ||
| General | 1 | 0 | ||
| All shared boards | 1 | 6 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index01
| Benchmark | Mistral Large 4 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench coding | 60.0% | 87.4% | Qwen3.8 Flash |
| LMArena WebDev | 1543 | Not measured | Only Mistral Large 4 measured |
| Terminal-Bench 4 (Vals AI) | 27.8% | Not measured | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | 78.4% | Not measured | Only Mistral Large 4 measured |
| Code migration (Vals AI) | 30.6% | Not measured | Only Mistral Large 4 measured |
| IOI (Vals AI) | 45.3% | Not measured | Only Mistral Large 4 measured |
| SWE-bench Multimodal (Vals AI) | 33.1% | Not measured | Only Mistral Large 4 measured |
| Vibe Code Bench 1-100 (Vals AI) | 14.3% | Not measured | Only Mistral Large 4 measured |
| SciCode | 54.2% | Not measured | Only Mistral Large 4 measured |
| FrontierCode | 39.4% | Not measured | Only Mistral Large 4 measured |
| ALE-Bench | 1213.2 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: coding | 1478 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: software and IT | 1467 | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev: React | 1559 | Not measured | Only Mistral Large 4 measured |
| LMArena WebDev: HTML | 1487 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 23 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | Not measured | Only Mistral Large 4 measured |
| Epoch Capabilities Index | 150.0 | Not measured | Only Mistral Large 4 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Mistral Large 4 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench research | 28.1% | 74.6% | Qwen3.8 Flash |
| LiveBench browser | 8.0% | 48.0% | Qwen3.8 Flash |
| LiveBench long agentic | 11.8% | 37.1% | Qwen3.8 Flash |
| Finance Agent (Vals AI) | 54.7% | Not measured | Only Mistral Large 4 measured |
| Tax Agent Bench (Vals AI) | 30.4% | Not measured | Only Mistral Large 4 measured |
| Legal Research Bench (Vals AI) | 31.7% | Not measured | Only Mistral Large 4 measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 17.5% | Not measured | Only Mistral Large 4 measured |
| Excel Modeling Benchmark (Vals AI) | 56.2% | Not measured | Only Mistral Large 4 measured |
| BioMysteryBench (Vals AI) | 67.0% | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 4 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench reasoning | 83.9% | 87.4% | Qwen3.8 Flash |
| MysteryMechanism (Vals AI) | 12.2% | Not measured | Only Mistral Large 4 measured |
| Humanity's Last Exam (Artificial Analysis run) | 35.0% | Not measured | Only Mistral Large 4 measured |
| GPQA Diamond (Epoch AI run) | 88.1% | Not measured | Only Mistral Large 4 measured |
| Chess puzzles | 33.0% | Not measured | Only Mistral Large 4 measured |
| Mystery game puzzles | 17.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | 1444 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: expert | 1444 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: hard prompts in English | 1442 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: diagrams | 1288 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 11 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| OTIS Mock AIME | 98.3% | Not measured | Only Mistral Large 4 measured |
| FrontierMath, tiers 1 to 3 | 58.6% | Not measured | Only Mistral Large 4 measured |
| FrontierMath, tier 4 | 26.8% | Not measured | Only Mistral Large 4 measured |
| ProofBench | 10.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: math | 1469 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: mathematical work | 1462 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 40.7% | Not measured | Only Mistral Large 4 measured |
| SimpleQA Verified | 20.0% | Not measured | Only Mistral Large 4 measured |
| LMArena Text: science | 1448 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: medicine and healthcare | 1433 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: legal and government | 1425 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: business and finance | 1439 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Mistral Large 4 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| Design Arena: websites | 1258 | Not measured | Only Mistral Large 4 measured |
| Design Arena: UI components | 1275 | Not measured | Only Mistral Large 4 measured |
| Design Arena: game dev | 1226 | Not measured | Only Mistral Large 4 measured |
| Design Arena: data viz | 1274 | Not measured | Only Mistral Large 4 measured |
| Design Arena: 3D | 1253 | Not measured | Only Mistral Large 4 measured |
| Design Arena: all code categories | 1259 | Not measured | Only Mistral Large 4 measured |
| Design Arena: SVG | 1232 | Not measured | Only Mistral Large 4 measured |
| Design Arena: ASCII art | 1203 | Not measured | Only Mistral Large 4 measured |
| LiveBench design | 65.6% | 72.8% | Qwen3.8 Flash |
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Mistral Large 4 | Qwen3.8 Flash | Leader |
|---|---|---|---|
| LiveBench data analysis | 76.5% | 74.2% | Mistral Large 4 |
| MedScribe (Vals AI) | 80.4% | Not measured | Only Mistral Large 4 measured |
| Long context reasoning (AA-LCR) | 81.3% | Not measured | Only Mistral Large 4 measured |
| DTBench | 88.2% | Not measured | Only Mistral Large 4 measured |
| LMCA | 35.8% | Not measured | Only Mistral Large 4 measured |
| Surface Evolver Bench | 28.1% | Not measured | Only Mistral Large 4 measured |
| Furniture assembly | 20.8% | Not measured | Only Mistral Large 4 measured |
| LMArena Text | 1431 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: instruction following | 1422 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: creative writing | 1363 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision | 1272 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: English | 1433 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: non-English | 1422 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Chinese | 1492 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Japanese | 1415 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: French | 1492 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Spanish | 1455 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: Russian | 1417 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: multi-turn | 1435 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: longer queries | 1428 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: writing and language | 1386 | Not measured | Only Mistral Large 4 measured |
| LMArena Text: entertainment and media | 1378 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: English | 1283 | Not measured | Only Mistral Large 4 measured |
| LMArena Vision: reading text | 1284 | Not measured | Only Mistral Large 4 measured |
| Neither model has a result on the other 22 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Mistral Large 4 | Qwen3.8 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
Qwen3.8 Flash costs less
Repository review
50K input + 3K output tokens
Qwen3.8 Flash costs less
Agent loop
200K input + 10K output tokens
Qwen3.8 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 | Mistral Large 4 | Qwen3.8 Flash |
|---|---|---|
| Maker | Mistral AI | Qwen |
| Weights | No public weights listed | Open weights |
| Released | October 6, 2026 | August 26, 2026 |
| Context window | 1.05M | 1M |
| Input $/Mtok | $1.36 | $0.15 |
| Output $/Mtok | $4.18 | $0.47 |
| Coding index | 55.3 | 87.4 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Mistral Large 4 better than Qwen3.8 Flash for coding?
Pick Qwen3.8 Flash for coding: it scores 87.4 on the Vibe Coding Index against 55.3 for Mistral Large 4, though on 1 benchmark against 2. Pick Mistral Large 4 when the context window is larger, 1.05M against 1M tokens, or when the benchmark that matters is LiveBench data analysis, where it leads.
Which is cheaper, Mistral Large 4 or Qwen3.8 Flash?
Mistral Large 4 costs $1.36 per million input tokens and $4.18 per million output tokens; Qwen3.8 Flash costs $0.15 and $0.47. Cost per solved task is known for neither of them.
Which has the bigger context window, Mistral Large 4 or Qwen3.8 Flash?
Mistral Large 4, with 1.05M tokens against 1M.
How many benchmarks is the Mistral Large 4 vs Qwen3.8 Flash comparison based on?
7 benchmarks have a result for both models as of October 21, 2026. Mistral Large 4's coding index rests on 2 independent benchmarks and Qwen3.8 Flash's on 1. Where only one model has a result, the page says so instead of naming a winner.