Ling 3.0 Flash vs Mistral Large 4
Mistral Large 4 leads Ling 3.0 Flash on coding, 56.4 to 29.6 on the Vibe Coding Index, and Ling 3.0 Flash costs 34.4x less per output token ($0.1215 vs $4.18 per million). Updated October 22, 2026; 11 benchmarks have a result for both.
Ling 3.0 Flash or Mistral Large 4: which to pick
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash.
Pick Ling 3.0 Flash for output tokens 34.4x cheaper ($0.1215 vs $4.18 per million) and work measured by MedScribe (Vals AI), where it leads.
- Shared results
- 11
- Ling 3.0 Flash only
- 13
- Mistral Large 4 only
- 70
- 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
Mistral Large 4
Mistral Large 4 scores 56.4 against 29.6.
2 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
Mistral Large 4
Mistral Large 4 leads, 38.4 against 20.1.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only Ling 3.0 Flash has a AA Agentic Index result, 19.3.
Directional only
Reasoning
GPQA Diamond
No call
Only Ling 3.0 Flash has a GPQA Diamond result, 84.8%.
Directional only
Knowledge
MMLU Pro
No call
Only Ling 3.0 Flash has a MMLU Pro result, 82.0%.
Directional only
Web design
Design Arena: websites
No call
Only Mistral Large 4 has a Design Arena: websites result, 1257.
Directional only
Long documents
Listed context window
Mistral Large 4
Mistral Large 4 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ling 3.0 Flash
Ling 3.0 Flash $0.0001, Mistral Large 4 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Ling 3.0 Flash has the number, $0.05.
Directional only
At a glance
- Coding index
- Ling 3.0 Flash 29.6 from 2 benchmarks, Mistral Large 4 56.4 from 5 benchmarks.
- Widest category
- Coding, 39.4 points apart on average over 3 shared benchmarks.
- Widest single gap
- Vibe Code Bench (Vals AI): Ling 3.0 Flash 2.9% against Mistral Large 4 78.4%, 75.5 points apart on a 0 to 100 scale.
- Output price
- Ling 3.0 Flash $0.1215 against Mistral Large 4 $4.18 per million output tokens, 34.4x apart.
- Context window
- Ling 3.0 Flash takes 262K tokens, Mistral Large 4 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 | Ling 3.0 Flash | Bars | Mistral Large 4 | Ties |
|---|---|---|---|---|
| Coding | 0 | 3 | ||
| Intelligence | 0 | 1 | ||
| Agentic work | 0 | 3 | ||
| Reasoning | 0 | 1 | ||
| Knowledge | 0 | 1 | ||
| General | 1 | 1 | ||
| All shared boards | 1 | 10 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
| Benchmark | Ling 3.0 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 60.0% | Only Mistral Large 4 measured |
| LMArena WebDev | Not measured | 1543 | Only Mistral Large 4 measured |
| AA Coding Index | 50.6 | Not measured | Only Ling 3.0 Flash measured |
| LiveCodeBench (Vals AI) | 84.0% | Not measured | Only Ling 3.0 Flash measured |
| SWE-bench Verified (Vals AI) | 65.2% | Not measured | Only Ling 3.0 Flash measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 27.8% | Only Mistral Large 4 measured |
| Vibe Code Bench (Vals AI) | 2.9% | 78.4% | Mistral Large 4 |
| Code migration (Vals AI) | 0.0% | 30.6% | Mistral Large 4 |
| IOI (Vals AI) | Not measured | 45.3% | Only Mistral Large 4 measured |
| Terminal-Bench 2.1 (Vals AI) | 50.2% | Not measured | Only Ling 3.0 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) | 27.9% | Not measured | Only Ling 3.0 Flash measured |
| SciCode | 42.0% | 54.2% | Mistral Large 4 |
| FrontierCode | Not measured | 39.4% | Only Mistral Large 4 measured |
| ALE-Bench | Not measured | 1213.2 | Only Mistral Large 4 measured |
| LMArena Text: coding | Not measured | 1478 | Only Mistral Large 4 measured |
| LMArena Text: software and IT | Not measured | 1467 | Only Mistral Large 4 measured |
| LMArena WebDev: React | Not measured | 1559 | Only Mistral Large 4 measured |
| LMArena WebDev: HTML | Not measured | 1487 | Only Mistral Large 4 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Intelligence Index | 20.1 | 38.4 | Mistral Large 4 |
| Epoch Capabilities Index | Not measured | 150.0 | Only Mistral Large 4 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index03
| Benchmark | Ling 3.0 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| AA Agentic Index | 19.3 | Not measured | Only Ling 3.0 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) | 30.3% | 54.7% | Mistral Large 4 |
| Tax Agent Bench (Vals AI) | Not measured | 30.4% | Only Mistral Large 4 measured |
| Legal Research Bench (Vals AI) | 0.0% | 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) | 25.0% | 56.2% | Mistral Large 4 |
| BioMysteryBench (Vals AI) | Not measured | 67.0% | Only Mistral Large 4 measured |
| Neither model has a result on the other 31 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| GPQA Diamond | 84.8% | Not measured | Only Ling 3.0 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 |
| GPQA Diamond (Artificial Analysis run) | 85.5% | Not measured | Only Ling 3.0 Flash measured |
| Humanity's Last Exam (Artificial Analysis run) | 23.7% | 35.0% | Mistral Large 4 |
| GPQA Diamond (Epoch AI run) | Not measured | 88.1% | Only Mistral Large 4 measured |
| Chess puzzles | Not measured | 33.0% | Only Mistral Large 4 measured |
| Mystery game puzzles | Not measured | 17.0% | Only Mistral Large 4 measured |
| LMArena Text: hard prompts | Not measured | 1444 | Only Mistral Large 4 measured |
| LMArena Text: expert | Not measured | 1444 | Only Mistral Large 4 measured |
| LMArena Text: hard prompts in English | Not measured | 1442 | Only Mistral Large 4 measured |
| LMArena Vision: diagrams | Not measured | 1288 | Only Mistral Large 4 measured |
| Neither model has a result on the other 10 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Ling 3.0 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| OTIS Mock AIME | Not measured | 98.3% | Only Mistral Large 4 measured |
| FrontierMath, tiers 1 to 3 | Not measured | 58.6% | Only Mistral Large 4 measured |
| FrontierMath, tier 4 | Not measured | 26.8% | Only Mistral Large 4 measured |
| ProofBench | Not measured | 10.0% | Only Mistral Large 4 measured |
| LMArena Text: math | Not measured | 1469 | Only Mistral Large 4 measured |
| LMArena Text: mathematical work | Not measured | 1462 | Only Mistral Large 4 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Ling 3.0 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| MMLU Pro | 82.0% | Not measured | Only Ling 3.0 Flash measured |
| LegalBench (Vals AI) | 79.7% | Not measured | Only Ling 3.0 Flash measured |
| CorpFin (Vals AI) | 61.9% | Not measured | Only Ling 3.0 Flash measured |
| TaxEval (Vals AI) | 70.7% | Not measured | Only Ling 3.0 Flash measured |
| MedCode (Vals AI) | 32.3% | 40.7% | Mistral Large 4 |
| SimpleQA Verified | Not measured | 20.0% | Only Mistral Large 4 measured |
| LMArena Text: science | Not measured | 1448 | Only Mistral Large 4 measured |
| LMArena Text: medicine and healthcare | Not measured | 1433 | Only Mistral Large 4 measured |
| LMArena Text: legal and government | Not measured | 1425 | Only Mistral Large 4 measured |
| LMArena Text: business and finance | Not measured | 1439 | Only Mistral Large 4 measured |
| Neither model has a result on the other 8 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
| Benchmark | Ling 3.0 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1257 | Only Mistral Large 4 measured |
| Design Arena: UI components | Not measured | 1272 | Only Mistral Large 4 measured |
| Design Arena: game dev | Not measured | 1225 | Only Mistral Large 4 measured |
| Design Arena: data viz | Not measured | 1275 | Only Mistral Large 4 measured |
| Design Arena: 3D | Not measured | 1252 | Only Mistral Large 4 measured |
| Design Arena: all code categories | Not measured | 1259 | Only Mistral Large 4 measured |
| Design Arena: SVG | Not measured | 1232 | Only Mistral Large 4 measured |
| Design Arena: ASCII art | Not measured | 1202 | Only Mistral Large 4 measured |
| LiveBench design | Not measured | 65.6% | Only Mistral Large 4 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Ling 3.0 Flash | Mistral Large 4 | Leader |
|---|---|---|---|
| LiveBench data analysis | Not measured | 76.5% | Only Mistral Large 4 measured |
| Public Benefits Bench (Vals AI) | 50.7% | Not measured | Only Ling 3.0 Flash measured |
| MedScribe (Vals AI) | 80.9% | 80.4% | Ling 3.0 Flash |
| Long context reasoning (AA-LCR) | 73.0% | 81.3% | Mistral Large 4 |
| DTBench | Not measured | 88.2% | Only Mistral Large 4 measured |
| LMCA | Not measured | 35.8% | Only Mistral Large 4 measured |
| Surface Evolver Bench | Not measured | 28.1% | Only Mistral Large 4 measured |
| Furniture assembly | Not measured | 20.8% | Only Mistral Large 4 measured |
| LMArena Text | Not measured | 1431 | Only Mistral Large 4 measured |
| LMArena Text: instruction following | Not measured | 1422 | Only Mistral Large 4 measured |
| LMArena Text: creative writing | Not measured | 1363 | Only Mistral Large 4 measured |
| LMArena Vision | Not measured | 1272 | Only Mistral Large 4 measured |
| LMArena Text: English | Not measured | 1433 | Only Mistral Large 4 measured |
| LMArena Text: non-English | Not measured | 1422 | Only Mistral Large 4 measured |
| LMArena Text: Chinese | Not measured | 1492 | Only Mistral Large 4 measured |
| LMArena Text: Japanese | Not measured | 1415 | Only Mistral Large 4 measured |
| LMArena Text: French | Not measured | 1492 | Only Mistral Large 4 measured |
| LMArena Text: Spanish | Not measured | 1455 | Only Mistral Large 4 measured |
| LMArena Text: Russian | Not measured | 1417 | Only Mistral Large 4 measured |
| LMArena Text: multi-turn | Not measured | 1435 | Only Mistral Large 4 measured |
| LMArena Text: longer queries | Not measured | 1428 | Only Mistral Large 4 measured |
| LMArena Text: writing and language | Not measured | 1386 | Only Mistral Large 4 measured |
| LMArena Text: entertainment and media | Not measured | 1378 | Only Mistral Large 4 measured |
| LMArena Vision: English | Not measured | 1283 | Only Mistral Large 4 measured |
| LMArena Vision: reading text | Not measured | 1284 | Only Mistral Large 4 measured |
| Neither model has a result on the other 21 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Ling 3.0 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
Ling 3.0 Flash costs less
Repository review
50K input + 3K output tokens
Ling 3.0 Flash costs less
Agent loop
200K input + 10K output tokens
Ling 3.0 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 | inclusionAI Ling 3.0 Flash | Mistral Large 4 |
|---|---|---|
| Maker | inclusionAI | Mistral AI |
| Weights | Open weights | No public weights listed |
| Released | July 23, 2026 | October 6, 2026 |
| Context window | 262K | 1.05M |
| Input $/Mtok | $0.0405 | $1.36 |
| Output $/Mtok | $0.1215 | $4.18 |
| Coding index | 29.6 | 56.4 |
| Independent measurements behind it | 2 | 5 |
| Cost per solved task | $0.05 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Ling 3.0 Flash better than Mistral Large 4 for coding?
Pick Mistral Large 4 for coding: it scores 56.4 on the Vibe Coding Index against 29.6 for Ling 3.0 Flash. Pick Ling 3.0 Flash for output tokens 34.4x cheaper ($0.1215 vs $4.18 per million) and work measured by MedScribe (Vals AI), where it leads.
Which is cheaper, Ling 3.0 Flash or Mistral Large 4?
Ling 3.0 Flash costs $0.0405 per million input tokens and $0.1215 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for Ling 3.0 Flash only.
Which has the bigger context window, Ling 3.0 Flash or Mistral Large 4?
Mistral Large 4, with 1.05M tokens against 262K.
How many benchmarks is the Ling 3.0 Flash vs Mistral Large 4 comparison based on?
11 benchmarks have a result for both models as of October 22, 2026. Ling 3.0 Flash's coding index rests on 2 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.