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Mistral Medium 3.5 vs Qwen3 Coder 480B A35B

Updated October 21, 2026. 43 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Mistral Medium 3.5 Replace Qwen3 Coder 480B A35B
Mistral Medium 3.5Mistral AI
Coding
9.2
Overall
14.2
Output $/M
$7.50
37
Qwen3 Coder 480B A35BQwen
Coding
50.0
Overall
11.9
Output $/M
$1.00
6
vs boards won of 43 shared

Decision reading

Pick Qwen3 Coder 480B A35B for coding: it scores 50.0 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5.

Pick Mistral Medium 3.5 when what matters is Terminal-Bench Hard (Artificial Analysis run) or ALE-Bench, where it leads.

Model AMistral Medium 3.5Mistral AI9.2/1001 independent benchmark$6.02 per solved taskModel BQwen3 Coder 480B A35BQwen50.0/1002 independent benchmarksNo cost per solved task
Shared results
43
Mistral Medium 3.5 only
37
Qwen3 Coder 480B A35B only
9
Like-for-like categories
8 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.

At a glance

Coding index
Mistral Medium 3.5 9.2 from 1 benchmark, Qwen3 Coder 480B A35B 50.0 from 2 benchmarks.
Widest category
Agentic work, 50.6 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Mistral Medium 3.5 94.2% against Qwen3 Coder 480B A35B 43.6%, 50.6 points apart on a 0 to 100 scale.
Output price
Mistral Medium 3.5 $7.50 against Qwen3 Coder 480B A35B $1.00 per million output tokens, 7.5x apart.
Context window
Both take 262K tokens.

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
CategoryMistral Medium 3.5BarsQwen3 Coder 480B A35BTies
Coding52
Intelligence10
Agentic work10
Reasoning50
Math20
Knowledge40
Web design14
General180
All shared boards376
CodingLike-for-likeFour of these boards feed the Vibe Coding Index52
Coding benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
SWE-bench VerifiedNot measured69.6%Only Qwen3 Coder 480B A35B measured
LMArena WebDev12641275Qwen3 Coder 480B A35B
AA Coding Index46.9Not measuredOnly Mistral Medium 3.5 measured
SWE-bench Verified (Vals AI)66.4%Not measuredOnly Mistral Medium 3.5 measured
Vibe Code Bench (Vals AI)2.9%Not measuredOnly Mistral Medium 3.5 measured
Code migration (Vals AI)5.1%Not measuredOnly Mistral Medium 3.5 measured
Terminal-Bench 2.1 (Vals AI)39.0%Not measuredOnly Mistral Medium 3.5 measured
LiveCodeBench (Artificial Analysis run)Not measured58.5%Only Qwen3 Coder 480B A35B measured
SciCode40.2%Not measuredOnly Mistral Medium 3.5 measured
Terminal-Bench Hard (Artificial Analysis run)33.3%18.9%Mistral Medium 3.5
Terminal-BenchNot measured27.2%Only Qwen3 Coder 480B A35B measured
GSO-BenchNot measured4.9%Only Qwen3 Coder 480B A35B measured
WeirdMLNot measured41.2%Only Qwen3 Coder 480B A35B measured
ALE-Bench764.0461.4Mistral Medium 3.5
LMArena Text: coding14601412Mistral Medium 3.5
LMArena Text: software and IT14581393Mistral Medium 3.5
LMArena WebDev: React12541257Qwen3 Coder 480B A35B
LMArena WebDev: HTML13081287Mistral Medium 3.5
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
AA Intelligence Index14.211.9Mistral Medium 3.5
Epoch Capabilities Index141.4Not measuredOnly Mistral Medium 3.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
AA Agentic Index7.0Not measuredOnly Mistral Medium 3.5 measured
Finance Agent (Vals AI)32.1%Not measuredOnly Mistral Medium 3.5 measured
Tax Agent Bench (Vals AI)4.5%Not measuredOnly Mistral Medium 3.5 measured
Legal Research Bench (Vals AI)9.1%Not measuredOnly Mistral Medium 3.5 measured
Excel Modeling Benchmark (Vals AI)11.2%Not measuredOnly Mistral Medium 3.5 measured
τ²-Bench Telecom94.2%43.6%Mistral Medium 3.5
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
GPQA Diamond34.9%Not measuredOnly Mistral Medium 3.5 measured
GPQA Diamond (Artificial Analysis run)74.8%61.8%Mistral Medium 3.5
Humanity's Last Exam (Artificial Analysis run)13.8%4.5%Mistral Medium 3.5
LMArena Text: hard prompts14361372Mistral Medium 3.5
LMArena Text: expert14321338Mistral Medium 3.5
LMArena Text: hard prompts in English14451380Mistral Medium 3.5
LMArena Vision: diagrams1254Not measuredOnly Mistral Medium 3.5 measured
LMArena Vision: homework1230Not measuredOnly Mistral Medium 3.5 measured
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
AA Math IndexNot measured39.3Only Qwen3 Coder 480B A35B measured
AIME 2025 (Artificial Analysis run)Not measured39.3%Only Qwen3 Coder 480B A35B measured
ProofBench9.0%Not measuredOnly Mistral Medium 3.5 measured
LMArena Text: math14311365Mistral Medium 3.5
LMArena Text: mathematical work14401367Mistral Medium 3.5
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
MMLU Pro75.3%Not measuredOnly Mistral Medium 3.5 measured
CaseLaw (Vals AI)44.2%Not measuredOnly Mistral Medium 3.5 measured
CorpFin (Vals AI)58.8%Not measuredOnly Mistral Medium 3.5 measured
TaxEval (Vals AI)68.0%Not measuredOnly Mistral Medium 3.5 measured
MortgageTax (Vals AI)28.9%Not measuredOnly Mistral Medium 3.5 measured
MedCode (Vals AI)33.8%Not measuredOnly Mistral Medium 3.5 measured
MMLU Pro (Artificial Analysis run)Not measured78.8%Only Qwen3 Coder 480B A35B measured
LMArena Text: science14281347Mistral Medium 3.5
LMArena Text: medicine and healthcare14091347Mistral Medium 3.5
LMArena Text: legal and government14371358Mistral Medium 3.5
LMArena Text: business and finance14261343Mistral Medium 3.5
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index14
Web design benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
Design Arena: websites11421159Qwen3 Coder 480B A35B
Design Arena: UI components10791112Qwen3 Coder 480B A35B
Design Arena: game dev10791099Qwen3 Coder 480B A35B
Design Arena: data viz11201084Mistral Medium 3.5
Design Arena: 3D1061Not measuredOnly Mistral Medium 3.5 measured
Design Arena: all code categories11221143Qwen3 Coder 480B A35B
Design Arena: SVG949Not measuredOnly Mistral Medium 3.5 measured
Design Arena: ASCII art1062Not measuredOnly Mistral Medium 3.5 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index180
General benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
SAGE (Vals AI)37.6%Not measuredOnly Mistral Medium 3.5 measured
MedScribe (Vals AI)67.7%Not measuredOnly Mistral Medium 3.5 measured
Vals Multimodal Index34.8%Not measuredOnly Mistral Medium 3.5 measured
IFBench68.8%40.5%Mistral Medium 3.5
Long context reasoning (AA-LCR)69.3%45.7%Mistral Medium 3.5
DTBench75.5%Not measuredOnly Mistral Medium 3.5 measured
LMCA26.1%Not measuredOnly Mistral Medium 3.5 measured
Surface Evolver Bench26.9%Not measuredOnly Mistral Medium 3.5 measured
LMArena Text14211357Mistral Medium 3.5
LMArena Text: instruction following14151355Mistral Medium 3.5
LMArena Text: creative writing13741333Mistral Medium 3.5
LMArena Vision1222Not measuredOnly Mistral Medium 3.5 measured
LMArena Text: English14331359Mistral Medium 3.5
LMArena Text: non-English14041346Mistral Medium 3.5
LMArena Text: Chinese14441357Mistral Medium 3.5
LMArena Text: German14531325Mistral Medium 3.5
LMArena Text: JapaneseNot measured1311Only Qwen3 Coder 480B A35B measured
LMArena Text: Korean13841305Mistral Medium 3.5
LMArena Text: French14481398Mistral Medium 3.5
LMArena Text: Spanish14111360Mistral Medium 3.5
LMArena Text: Russian13951366Mistral Medium 3.5
LMArena Text: Polish14301344Mistral Medium 3.5
LMArena Text: multi-turn14231366Mistral Medium 3.5
LMArena Text: longer queries14151378Mistral Medium 3.5
LMArena Text: writing and language13841340Mistral Medium 3.5
LMArena Text: entertainment and media13821317Mistral Medium 3.5
LMArena Vision: English1240Not measuredOnly Mistral Medium 3.5 measured
LMArena Vision: Chinese1244Not measuredOnly Mistral Medium 3.5 measured
LMArena Vision: reading text1233Not measuredOnly Mistral Medium 3.5 measured
LMArena Vision: humor1216Not measuredOnly Mistral Medium 3.5 measured
LMArena Vision: creative writing1198Not measuredOnly Mistral Medium 3.5 measured
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Mistral Medium 3.5 and Qwen3 Coder 480B A35B
BenchmarkMistral Medium 3.5Qwen3 Coder 480B A35BLeader
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 Medium 3.5$0.0053Fits in one request
Qwen3 Coder 480B A35B$0.0008Fits in one request

Qwen3 Coder 480B A35B costs less

Repository review

50K input + 3K output tokens

Mistral Medium 3.5$0.098Fits in one request
Qwen3 Coder 480B A35B$0.018Fits in one request

Qwen3 Coder 480B A35B costs less

Agent loop

200K input + 10K output tokens

Mistral Medium 3.5$0.375Fits in one request
Qwen3 Coder 480B A35B$0.070Fits in one request

Qwen3 Coder 480B A35B 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 Mistral Medium 3.5 and Qwen3 Coder 480B A35B
SpecificationMistral Medium 3.5Qwen3 Coder 480B A35B
MakerMistral AIQwen
WeightsNo public weights listedOpen weights
ReleasedApril 30, 2026July 23, 2025
Context window262K262K
Input $/Mtok$1.50$0.30
Output $/Mtok$7.50$1.00
Coding index9.250.0
Independent measurements behind it12
Cost per solved task$6.02Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Mistral Medium 3.5 better than Qwen3 Coder 480B A35B for coding?

Pick Qwen3 Coder 480B A35B for coding: it scores 50.0 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5. Pick Mistral Medium 3.5 when what matters is Terminal-Bench Hard (Artificial Analysis run) or ALE-Bench, where it leads.

Which is cheaper, Mistral Medium 3.5 or Qwen3 Coder 480B A35B?

Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; Qwen3 Coder 480B A35B costs $0.30 and $1.00. Cost per solved task is known for Mistral Medium 3.5 only.

Which has the bigger context window, Mistral Medium 3.5 or Qwen3 Coder 480B A35B?

Neither: both take 262K tokens.

How many benchmarks is the Mistral Medium 3.5 vs Qwen3 Coder 480B A35B comparison based on?

43 benchmarks have a result for both models as of October 21, 2026. Mistral Medium 3.5's coding index rests on 1 independent benchmark and Qwen3 Coder 480B A35B's on 2. Where only one model has a result, the page says so instead of naming a winner.

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