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Mistral Medium 3.5 vs Qwen3.5-Flash

Qwen3.5-Flash leads Mistral Medium 3.5 on coding, 41.1 to 25.5 on the Vibe Coding Index, and Qwen3.5-Flash costs 28.8x less per output token ($0.26 vs $7.50 per million). Updated October 22, 2026; 44 benchmarks have a result for both.

Replace Mistral Medium 3.5 Replace Qwen3.5-Flash
Mistral Medium 3.5Mistral AI
Coding
25.5
Overall
37.3
Output $/M
$7.50
32
Qwen3.5-FlashQwen
Coding
41.1
Overall
50.1
Output $/M
$0.26
12
vs boards won of 44 shared

Mistral Medium 3.5 or Qwen3.5-Flash: which to pick

Pick Qwen3.5-Flash for coding: it scores 41.1 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5, though on 2 benchmarks against 3.

Pick Mistral Medium 3.5 for work measured by LMArena WebDev or SWE-bench Verified (Vals AI), where it leads.

Model AMistral Medium 3.5Mistral AI25.5/1003 independent benchmarks$6.02 per solved taskModel BQwen3.5-FlashQwen41.1/1002 independent benchmarks$0.40 per solved task
Shared results
44
Mistral Medium 3.5 only
37
Qwen3.5-Flash only
11
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.

At a glance

Coding index
Mistral Medium 3.5 25.5 from 3 benchmarks, Qwen3.5-Flash 41.1 from 2 benchmarks.
Widest category
Reasoning, 15.9 points apart on average over 4 shared benchmarks.
Widest single gap
GPQA Diamond: Mistral Medium 3.5 34.9% against Qwen3.5-Flash 82.8%, 48.0 points apart on a 0 to 100 scale.
Output price
Mistral Medium 3.5 $7.50 against Qwen3.5-Flash $0.26 per million output tokens, 28.8x apart.
Context window
Mistral Medium 3.5 takes 262K tokens, Qwen3.5-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.

Boards won, where both have a result
CategoryMistral Medium 3.5BarsQwen3.5-FlashTies
Coding70
Intelligence01
Reasoning31
Math20
Knowledge55
General155
All shared boards3212
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for Mistral Medium 3.5 and Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
LMArena WebDev12641244Mistral Medium 3.5
AA Coding Index46.9Not measuredOnly Mistral Medium 3.5 measured
LiveCodeBench (Vals AI)Not measured83.3%Only Qwen3.5-Flash measured
SWE-bench Verified (Vals AI)66.4%64.4%Mistral Medium 3.5
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
SciCode40.2%Not measuredOnly Mistral Medium 3.5 measured
Terminal-Bench Hard (Artificial Analysis run)33.3%Not measuredOnly Mistral Medium 3.5 measured
ALE-Bench764.0265.9Mistral Medium 3.5
LMArena Text: coding14601412Mistral Medium 3.5
LMArena Text: software and IT14581416Mistral Medium 3.5
LMArena WebDev: React12541229Mistral Medium 3.5
LMArena WebDev: HTML13081291Mistral Medium 3.5
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Mistral Medium 3.5 and Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
AA Intelligence Index14.2Not measuredOnly Mistral Medium 3.5 measured
Epoch Capabilities Index141.4143.5Qwen3.5-Flash
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Agentic work benchmarks for Mistral Medium 3.5 and Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
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%Not measuredOnly Mistral Medium 3.5 measured
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index31
Reasoning benchmarks for Mistral Medium 3.5 and Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
GPQA Diamond34.9%82.8%Qwen3.5-Flash
MMMU Pro (Vals AI)Not measured81.9%Only Qwen3.5-Flash measured
GPQA Diamond (Artificial Analysis run)74.8%Not measuredOnly Mistral Medium 3.5 measured
Humanity's Last Exam (Artificial Analysis run)13.8%Not measuredOnly Mistral Medium 3.5 measured
GPQA Diamond (Epoch AI run)Not measured82.3%Only Qwen3.5-Flash measured
Chess puzzlesNot measured14.0%Only Qwen3.5-Flash measured
Mystery game puzzlesNot measured20.0%Only Qwen3.5-Flash measured
LMArena Text: hard prompts14361403Mistral Medium 3.5
LMArena Text: expert14321407Mistral Medium 3.5
LMArena Text: hard prompts in English14451409Mistral Medium 3.5
LMArena Vision: diagrams1254Not measuredOnly Mistral Medium 3.5 measured
LMArena Vision: homework1230Not measuredOnly Mistral Medium 3.5 measured
Kagi LLM Benchmark41.4%Not measuredOnly Mistral Medium 3.5 measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Mistral Medium 3.5 and Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
AIMENot measured92.5%Only Qwen3.5-Flash measured
OTIS Mock AIMENot measured84.4%Only Qwen3.5-Flash measured
FrontierMath, tiers 1 to 3Not measured18.2%Only Qwen3.5-Flash measured
ProofBench9.0%Not measuredOnly Mistral Medium 3.5 measured
LMArena Text: math14311407Mistral Medium 3.5
LMArena Text: mathematical work14401413Mistral Medium 3.5
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index55
Knowledge benchmarks for Mistral Medium 3.5 and Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
MMLU Pro75.3%84.1%Qwen3.5-Flash
LegalBench (Vals AI)Not measured84.3%Only Qwen3.5-Flash measured
CaseLaw (Vals AI)44.2%56.0%Qwen3.5-Flash
CorpFin (Vals AI)58.8%63.6%Qwen3.5-Flash
TaxEval (Vals AI)68.0%72.2%Qwen3.5-Flash
MortgageTax (Vals AI)28.9%67.4%Qwen3.5-Flash
MedCode (Vals AI)33.8%33.0%Mistral Medium 3.5
SimpleQA VerifiedNot measured20.3%Only Qwen3.5-Flash measured
LMArena Text: science14281415Mistral Medium 3.5
LMArena Text: medicine and healthcare14091407Mistral Medium 3.5
LMArena Text: legal and government14371398Mistral Medium 3.5
LMArena Text: business and finance14261394Mistral Medium 3.5
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Mistral Medium 3.5 and Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
Design Arena: websites1142Not measuredOnly Mistral Medium 3.5 measured
Design Arena: UI components1076Not measuredOnly Mistral Medium 3.5 measured
Design Arena: game dev1079Not measuredOnly Mistral Medium 3.5 measured
Design Arena: data viz1120Not measuredOnly Mistral Medium 3.5 measured
Design Arena: 3D1060Not measuredOnly Mistral Medium 3.5 measured
Design Arena: all code categories1121Not measuredOnly Mistral Medium 3.5 measured
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 index155
General benchmarks for Mistral Medium 3.5 and Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
SAGE (Vals AI)37.6%42.5%Qwen3.5-Flash
MedScribe (Vals AI)67.7%70.6%Qwen3.5-Flash
Vals Multimodal Index34.8%Not measuredOnly Mistral Medium 3.5 measured
IFBench68.8%Not measuredOnly Mistral Medium 3.5 measured
Long context reasoning (AA-LCR)69.3%Not measuredOnly Mistral Medium 3.5 measured
DTBench75.5%82.9%Qwen3.5-Flash
LMCA26.1%29.1%Qwen3.5-Flash
Surface Evolver Bench26.9%Not measuredOnly Mistral Medium 3.5 measured
LMArena Text14211397Mistral Medium 3.5
LMArena Text: instruction following14151374Mistral Medium 3.5
LMArena Text: creative writing13741343Mistral Medium 3.5
LMArena Vision1222Not measuredOnly Mistral Medium 3.5 measured
LMArena Text: English14331404Mistral Medium 3.5
LMArena Text: non-English14041385Mistral Medium 3.5
LMArena Text: Chinese14441445Qwen3.5-Flash
LMArena Text: German14531390Mistral Medium 3.5
LMArena Text: JapaneseNot measured1369Only Qwen3.5-Flash measured
LMArena Text: Korean13841344Mistral Medium 3.5
LMArena Text: French14481413Mistral Medium 3.5
LMArena Text: Spanish14111400Mistral Medium 3.5
LMArena Text: Russian13951380Mistral Medium 3.5
LMArena Text: Polish14301376Mistral Medium 3.5
LMArena Text: multi-turn14231393Mistral Medium 3.5
LMArena Text: longer queries14151392Mistral Medium 3.5
LMArena Text: writing and language13841369Mistral Medium 3.5
LMArena Text: entertainment and media13821347Mistral 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 Qwen3.5-Flash
BenchmarkMistral Medium 3.5Qwen3.5-FlashLeader
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
Qwen3.5-Flash$0.0002Fits in one request

Qwen3.5-Flash costs less

Repository review

50K input + 3K output tokens

Mistral Medium 3.5$0.098Fits in one request
Qwen3.5-Flash$0.0040Fits in one request

Qwen3.5-Flash costs less

Agent loop

200K input + 10K output tokens

Mistral Medium 3.5$0.375Fits in one request
Qwen3.5-Flash$0.016Fits in one request

Qwen3.5-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.

Specifications of Mistral Medium 3.5 and Qwen3.5-Flash
SpecificationMistral Medium 3.5Qwen3.5-Flash
MakerMistral AIQwen
WeightsNo public weights listedNo public weights listed
ReleasedApril 30, 2026February 25, 2026
Context window262K1M
Input $/Mtok$1.50$0.065
Output $/Mtok$7.50$0.26
Coding index25.541.1
Independent measurements behind it32
Cost per solved task$6.02$0.40
SourceOpenRouter listingOpenRouter listing

Questions

Is Mistral Medium 3.5 better than Qwen3.5-Flash for coding?

Pick Qwen3.5-Flash for coding: it scores 41.1 on the Vibe Coding Index against 25.5 for Mistral Medium 3.5, though on 2 benchmarks against 3. Pick Mistral Medium 3.5 for work measured by LMArena WebDev or SWE-bench Verified (Vals AI), where it leads.

Which is cheaper, Mistral Medium 3.5 or Qwen3.5-Flash?

Mistral Medium 3.5 costs $1.50 per million input tokens and $7.50 per million output tokens; Qwen3.5-Flash costs $0.065 and $0.26. Per solved SWE-bench Verified task, Mistral Medium 3.5 costs $6.02 and Qwen3.5-Flash $0.40.

Which has the bigger context window, Mistral Medium 3.5 or Qwen3.5-Flash?

Qwen3.5-Flash, with 1M tokens against 262K.

How many benchmarks is the Mistral Medium 3.5 vs Qwen3.5-Flash comparison based on?

44 benchmarks have a result for both models as of October 22, 2026. Mistral Medium 3.5's coding index rests on 3 independent benchmarks and Qwen3.5-Flash's on 2. Where only one model has a result, the page says so instead of naming a winner.

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