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Ling 3.0 Flash VL vs Mistral Large 4

Mistral Large 4 leads Ling 3.0 Flash VL on the Artificial Analysis Intelligence Index, 38.4 to 24.6, and Ling 3.0 Flash VL costs 23.2x less per output token ($0.18 vs $4.18 per million). Updated October 22, 2026; 4 benchmarks have a result for both.

Ling 3.0 Flash VLinclusionAI
Coding
No data
Overall
No data
Output $/M
$0.18
0
Mistral Large 4Mistral AI
Coding
56.4
Overall
54.6
Output $/M
$4.18
4
vs boards won of 4 shared

Ling 3.0 Flash VL or Mistral Large 4: which to pick

Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Ling 3.0 Flash VL has none, so the two cannot be ranked on coding.

Pick Ling 3.0 Flash VL for output tokens 23.2x cheaper ($0.18 vs $4.18 per million).

Shared results
4
Ling 3.0 Flash VL only
3
Mistral Large 4 only
78
Like-for-like categories
4 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.

At a glance

Coding index
Ling 3.0 Flash VL not benchmarked, Mistral Large 4 56.4 from 5 benchmarks.
Widest category
Intelligence, 13.8 points apart on average over 1 shared benchmark.
Widest single gap
AA Intelligence Index: Ling 3.0 Flash VL 24.6 against Mistral Large 4 38.4, 13.8 points apart on a 0 to 100 scale.
Output price
Ling 3.0 Flash VL $0.18 against Mistral Large 4 $4.18 per million output tokens, 23.2x apart.
Context window
Ling 3.0 Flash VL takes 131K 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.

Boards won, where both have a result
CategoryLing 3.0 Flash VLBarsMistral Large 4Ties
Coding01
Intelligence01
Reasoning01
General01
All shared boards04
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
Coding benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
LiveBench codingNot measured60.0%Only Mistral Large 4 measured
LMArena WebDevNot measured1543Only Mistral Large 4 measured
AA Coding Index57.0Not measuredOnly Ling 3.0 Flash VL measured
Terminal-Bench 4 (Vals AI)Not measured27.8%Only Mistral Large 4 measured
Vibe Code Bench (Vals AI)Not measured78.4%Only Mistral Large 4 measured
Code migration (Vals AI)Not measured30.6%Only Mistral Large 4 measured
IOI (Vals AI)Not measured45.3%Only Mistral Large 4 measured
SWE-bench Multimodal (Vals AI)Not measured33.1%Only Mistral Large 4 measured
Vibe Code Bench 1-100 (Vals AI)Not measured14.3%Only Mistral Large 4 measured
SciCode44.2%54.2%Mistral Large 4
FrontierCodeNot measured39.4%Only Mistral Large 4 measured
ALE-BenchNot measured1213.2Only Mistral Large 4 measured
LMArena Text: codingNot measured1478Only Mistral Large 4 measured
LMArena Text: software and ITNot measured1467Only Mistral Large 4 measured
LMArena WebDev: ReactNot measured1559Only Mistral Large 4 measured
LMArena WebDev: HTMLNot measured1487Only Mistral Large 4 measured
Neither model has a result on the other 27 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
AA Intelligence Index24.638.4Mistral Large 4
Epoch Capabilities IndexNot measured150.0Only Mistral Large 4 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index10 boards, none shared
Agentic work benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
AA Agentic Index28.7Not measuredOnly Ling 3.0 Flash VL measured
LiveBench researchNot measured28.1%Only Mistral Large 4 measured
LiveBench browserNot measured8.0%Only Mistral Large 4 measured
LiveBench long agenticNot measured11.8%Only Mistral Large 4 measured
Finance Agent (Vals AI)Not measured54.7%Only Mistral Large 4 measured
Tax Agent Bench (Vals AI)Not measured30.4%Only Mistral Large 4 measured
Legal Research Bench (Vals AI)Not measured31.7%Only Mistral Large 4 measured
Harvey's Legal Agent Benchmark (Vals AI)Not measured17.5%Only Mistral Large 4 measured
Excel Modeling Benchmark (Vals AI)Not measured56.2%Only Mistral Large 4 measured
BioMysteryBench (Vals AI)Not measured67.0%Only Mistral Large 4 measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index01
Reasoning benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
LiveBench reasoningNot measured83.9%Only Mistral Large 4 measured
MysteryMechanism (Vals AI)Not measured12.2%Only Mistral Large 4 measured
GPQA Diamond (Artificial Analysis run)86.2%Not measuredOnly Ling 3.0 Flash VL measured
Humanity's Last Exam (Artificial Analysis run)22.0%35.0%Mistral Large 4
GPQA Diamond (Epoch AI run)Not measured88.1%Only Mistral Large 4 measured
Chess puzzlesNot measured33.0%Only Mistral Large 4 measured
Mystery game puzzlesNot measured17.0%Only Mistral Large 4 measured
LMArena Text: hard promptsNot measured1444Only Mistral Large 4 measured
LMArena Text: expertNot measured1444Only Mistral Large 4 measured
LMArena Text: hard prompts in EnglishNot measured1442Only Mistral Large 4 measured
LMArena Vision: diagramsNot measured1288Only Mistral Large 4 measured
Neither model has a result on the other 12 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Math benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
OTIS Mock AIMENot measured98.3%Only Mistral Large 4 measured
FrontierMath, tiers 1 to 3Not measured58.6%Only Mistral Large 4 measured
FrontierMath, tier 4Not measured26.8%Only Mistral Large 4 measured
ProofBenchNot measured10.0%Only Mistral Large 4 measured
LMArena Text: mathNot measured1469Only Mistral Large 4 measured
LMArena Text: mathematical workNot measured1462Only Mistral Large 4 measured
MathArenaNot measured26.7%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
Knowledge benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
MedCode (Vals AI)Not measured40.7%Only Mistral Large 4 measured
SimpleQA VerifiedNot measured20.0%Only Mistral Large 4 measured
LMArena Text: scienceNot measured1448Only Mistral Large 4 measured
LMArena Text: medicine and healthcareNot measured1433Only Mistral Large 4 measured
LMArena Text: legal and governmentNot measured1425Only Mistral Large 4 measured
LMArena Text: business and financeNot measured1439Only Mistral Large 4 measured
Neither model has a result on the other 14 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
Design Arena: websitesNot measured1258Only Mistral Large 4 measured
Design Arena: UI componentsNot measured1273Only Mistral Large 4 measured
Design Arena: game devNot measured1225Only Mistral Large 4 measured
Design Arena: data vizNot measured1275Only Mistral Large 4 measured
Design Arena: 3DNot measured1252Only Mistral Large 4 measured
Design Arena: all code categoriesNot measured1259Only Mistral Large 4 measured
Design Arena: SVGNot measured1232Only Mistral Large 4 measured
Design Arena: ASCII artNot measured1202Only Mistral Large 4 measured
LiveBench designNot measured65.6%Only Mistral Large 4 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index01
General benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
LiveBench data analysisNot measured76.5%Only Mistral Large 4 measured
MedScribe (Vals AI)Not measured80.4%Only Mistral Large 4 measured
Long context reasoning (AA-LCR)78.3%81.3%Mistral Large 4
DTBenchNot measured88.2%Only Mistral Large 4 measured
LMCANot measured35.8%Only Mistral Large 4 measured
Surface Evolver BenchNot measured28.1%Only Mistral Large 4 measured
Furniture assemblyNot measured20.8%Only Mistral Large 4 measured
LMArena TextNot measured1431Only Mistral Large 4 measured
LMArena Text: instruction followingNot measured1422Only Mistral Large 4 measured
LMArena Text: creative writingNot measured1363Only Mistral Large 4 measured
LMArena VisionNot measured1272Only Mistral Large 4 measured
LMArena Text: EnglishNot measured1433Only Mistral Large 4 measured
LMArena Text: non-EnglishNot measured1422Only Mistral Large 4 measured
LMArena Text: ChineseNot measured1492Only Mistral Large 4 measured
LMArena Text: JapaneseNot measured1415Only Mistral Large 4 measured
LMArena Text: FrenchNot measured1492Only Mistral Large 4 measured
LMArena Text: SpanishNot measured1455Only Mistral Large 4 measured
LMArena Text: RussianNot measured1417Only Mistral Large 4 measured
LMArena Text: multi-turnNot measured1435Only Mistral Large 4 measured
LMArena Text: longer queriesNot measured1428Only Mistral Large 4 measured
LMArena Text: writing and languageNot measured1386Only Mistral Large 4 measured
LMArena Text: entertainment and mediaNot measured1378Only Mistral Large 4 measured
LMArena Vision: EnglishNot measured1283Only Mistral Large 4 measured
LMArena Vision: reading textNot measured1284Only Mistral Large 4 measured
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Ling 3.0 Flash VL and Mistral Large 4
BenchmarkLing 3.0 Flash VLMistral Large 4Leader
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 VL$0.0001Fits in one request
Mistral Large 4$0.0034Fits in one request

Ling 3.0 Flash VL costs less

Repository review

50K input + 3K output tokens

Ling 3.0 Flash VL$0.0035Fits in one request
Mistral Large 4$0.081Fits in one request

Ling 3.0 Flash VL costs less

Agent loop

200K input + 10K output tokens

Ling 3.0 Flash VL$0.014Exceeds the context window
Mistral Large 4$0.314Fits in one request

Ling 3.0 Flash VL 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.

Specifications of Ling 3.0 Flash VL and Mistral Large 4
SpecificationinclusionAI Ling 3.0 Flash VLMistral Large 4
MakerinclusionAIMistral AI
WeightsOpen weightsNo public weights listed
ReleasedSeptember 10, 2026October 6, 2026
Context window131K1.05M
Input $/Mtok$0.06$1.36
Output $/Mtok$0.18$4.18
Coding indexNot benchmarked56.4
Independent measurements behind it05
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Ling 3.0 Flash VL better than Mistral Large 4 for coding?

Only Mistral Large 4 has a coding score, 56.4 on the Vibe Coding Index; Ling 3.0 Flash VL has none, so the two cannot be ranked on coding. Pick Ling 3.0 Flash VL for output tokens 23.2x cheaper ($0.18 vs $4.18 per million).

Which is cheaper, Ling 3.0 Flash VL or Mistral Large 4?

Ling 3.0 Flash VL costs $0.06 per million input tokens and $0.18 per million output tokens; Mistral Large 4 costs $1.36 and $4.18. Cost per solved task is known for neither of them.

Which has the bigger context window, Ling 3.0 Flash VL or Mistral Large 4?

Mistral Large 4, with 1.05M tokens against 131K.

How many benchmarks is the Ling 3.0 Flash VL vs Mistral Large 4 comparison based on?

4 benchmarks have a result for both models as of October 22, 2026. Ling 3.0 Flash VL's coding index rests on 0 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.

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