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GLM 4.5 Air vs Mistral Medium 3.5

Mistral Medium 3.5 leads GLM 4.5 Air on the Artificial Analysis Intelligence Index, 14.2 to 11.1, and GLM 4.5 Air costs 6.8x less per output token ($1.10 vs $7.50 per million). Updated October 21, 2026; 42 benchmarks have a result for both.

Replace GLM 4.5 Air Replace Mistral Medium 3.5
GLM 4.5 AirZ.ai
Coding
No data
Overall
No data
Output $/M
$1.10
8
Mistral Medium 3.5Mistral AI
Coding
25.5
Overall
37.3
Output $/M
$7.50
34
vs boards won of 42 shared

GLM 4.5 Air or Mistral Medium 3.5: which to pick

Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; GLM 4.5 Air has none, so the two cannot be ranked on coding.

Pick GLM 4.5 Air for output tokens 6.8x cheaper ($1.10 vs $7.50 per million) and work measured by Kagi LLM Benchmark or Design Arena: websites, where it leads.

Model AGLM 4.5 AirZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Medium 3.5Mistral AI25.5/1003 independent benchmarks$6.02 per solved task
Shared results
42
GLM 4.5 Air only
6
Mistral Medium 3.5 only
39
Like-for-like categories
8 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
GLM 4.5 Air not benchmarked, Mistral Medium 3.5 25.5 from 3 benchmarks.
Widest category
Agentic work, 47.7 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: GLM 4.5 Air 46.5% against Mistral Medium 3.5 94.2%, 47.7 points apart on a 0 to 100 scale.
Output price
GLM 4.5 Air $1.10 against Mistral Medium 3.5 $7.50 per million output tokens, 6.8x apart.
Context window
GLM 4.5 Air takes 131K tokens, Mistral Medium 3.5 262K.

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
CategoryGLM 4.5 AirBarsMistral Medium 3.5Ties
Coding03
Intelligence01
Agentic work01
Reasoning15
Math02
Knowledge04
Web design70
General018
All shared boards834
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
LMArena WebDevNot measured1264Only Mistral Medium 3.5 measured
AA Coding IndexNot measured46.9Only Mistral Medium 3.5 measured
SWE-bench Verified (Vals AI)Not measured66.4%Only Mistral Medium 3.5 measured
Vibe Code Bench (Vals AI)Not measured2.9%Only Mistral Medium 3.5 measured
Code migration (Vals AI)Not measured5.1%Only Mistral Medium 3.5 measured
Terminal-Bench 2.1 (Vals AI)Not measured39.0%Only Mistral Medium 3.5 measured
LiveCodeBench (Artificial Analysis run)68.4%Not measuredOnly GLM 4.5 Air measured
SciCodeNot measured40.2%Only Mistral Medium 3.5 measured
Terminal-Bench Hard (Artificial Analysis run)20.5%33.3%Mistral Medium 3.5
GSO-Bench2.9%Not measuredOnly GLM 4.5 Air measured
ALE-BenchNot measured764.0Only Mistral Medium 3.5 measured
LMArena Text: coding13971460Mistral Medium 3.5
LMArena Text: software and IT14011458Mistral Medium 3.5
LMArena WebDev: ReactNot measured1254Only Mistral Medium 3.5 measured
LMArena WebDev: HTMLNot measured1308Only Mistral Medium 3.5 measured
Neither model has a result on the other 24 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
AA Intelligence Index11.114.2Mistral Medium 3.5
Epoch Capabilities IndexNot measured141.4Only Mistral Medium 3.5 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
AA Agentic IndexNot measured7.0Only Mistral Medium 3.5 measured
Finance Agent (Vals AI)Not measured32.1%Only Mistral Medium 3.5 measured
Tax Agent Bench (Vals AI)Not measured4.5%Only Mistral Medium 3.5 measured
Legal Research Bench (Vals AI)Not measured9.1%Only Mistral Medium 3.5 measured
Excel Modeling Benchmark (Vals AI)Not measured11.2%Only Mistral Medium 3.5 measured
τ²-Bench Telecom46.5%94.2%Mistral Medium 3.5
Neither model has a result on the other 35 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index15
Reasoning benchmarks for GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
GPQA DiamondNot measured34.9%Only Mistral Medium 3.5 measured
GPQA Diamond (Artificial Analysis run)73.3%74.8%Mistral Medium 3.5
Humanity's Last Exam (Artificial Analysis run)7.0%13.8%Mistral Medium 3.5
LMArena Text: hard prompts13791436Mistral Medium 3.5
LMArena Text: expert13701432Mistral Medium 3.5
LMArena Text: hard prompts in English13881445Mistral Medium 3.5
LMArena Vision: diagramsNot measured1254Only Mistral Medium 3.5 measured
LMArena Vision: homeworkNot measured1230Only Mistral Medium 3.5 measured
Kagi LLM Benchmark43.0%41.4%GLM 4.5 Air
Neither model has a result on the other 13 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
AA Math Index80.7Not measuredOnly GLM 4.5 Air measured
AIME 2025 (Artificial Analysis run)80.7%Not measuredOnly GLM 4.5 Air measured
ProofBenchNot measured9.0%Only Mistral Medium 3.5 measured
LMArena Text: math13961431Mistral Medium 3.5
LMArena Text: mathematical work13961440Mistral 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 index04
Knowledge benchmarks for GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
MMLU ProNot measured75.3%Only Mistral Medium 3.5 measured
CaseLaw (Vals AI)Not measured44.2%Only Mistral Medium 3.5 measured
CorpFin (Vals AI)Not measured58.8%Only Mistral Medium 3.5 measured
TaxEval (Vals AI)Not measured68.0%Only Mistral Medium 3.5 measured
MortgageTax (Vals AI)Not measured28.9%Only Mistral Medium 3.5 measured
MedCode (Vals AI)Not measured33.8%Only Mistral Medium 3.5 measured
MMLU Pro (Artificial Analysis run)81.5%Not measuredOnly GLM 4.5 Air measured
LMArena Text: science14071428Mistral Medium 3.5
LMArena Text: medicine and healthcare14021409Mistral Medium 3.5
LMArena Text: legal and government13821437Mistral Medium 3.5
LMArena Text: business and finance13711426Mistral Medium 3.5
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index70
Web design benchmarks for GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
Design Arena: websites11461142GLM 4.5 Air
Design Arena: UI components11231079GLM 4.5 Air
Design Arena: game dev10941079GLM 4.5 Air
Design Arena: data viz11861120GLM 4.5 Air
Design Arena: 3D11231061GLM 4.5 Air
Design Arena: all code categories11371121GLM 4.5 Air
Design Arena: SVG1071950GLM 4.5 Air
Design Arena: ASCII artNot measured1063Only 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 index018
General benchmarks for GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
SAGE (Vals AI)Not measured37.6%Only Mistral Medium 3.5 measured
MedScribe (Vals AI)Not measured67.7%Only Mistral Medium 3.5 measured
Vals Multimodal IndexNot measured34.8%Only Mistral Medium 3.5 measured
IFBench37.6%68.8%Mistral Medium 3.5
Long context reasoning (AA-LCR)46.7%69.3%Mistral Medium 3.5
DTBenchNot measured75.5%Only Mistral Medium 3.5 measured
LMCANot measured26.1%Only Mistral Medium 3.5 measured
Surface Evolver BenchNot measured26.9%Only Mistral Medium 3.5 measured
LMArena Text13841421Mistral Medium 3.5
LMArena Text: instruction following13541415Mistral Medium 3.5
LMArena Text: creative writing13431374Mistral Medium 3.5
LMArena VisionNot measured1222Only Mistral Medium 3.5 measured
LMArena Text: English13971433Mistral Medium 3.5
LMArena Text: non-English13661404Mistral Medium 3.5
LMArena Text: Chinese14261444Mistral Medium 3.5
LMArena Text: German13771453Mistral Medium 3.5
LMArena Text: Japanese1348Not measuredOnly GLM 4.5 Air measured
LMArena Text: Korean13081384Mistral Medium 3.5
LMArena Text: French14001448Mistral Medium 3.5
LMArena Text: Spanish13851411Mistral Medium 3.5
LMArena Text: Russian13731395Mistral Medium 3.5
LMArena Text: Polish13681430Mistral Medium 3.5
LMArena Text: multi-turn13711423Mistral Medium 3.5
LMArena Text: longer queries13661415Mistral Medium 3.5
LMArena Text: writing and language13541384Mistral Medium 3.5
LMArena Text: entertainment and media13391382Mistral Medium 3.5
LMArena Vision: EnglishNot measured1240Only Mistral Medium 3.5 measured
LMArena Vision: ChineseNot measured1244Only Mistral Medium 3.5 measured
LMArena Vision: reading textNot measured1233Only Mistral Medium 3.5 measured
LMArena Vision: humorNot measured1216Only Mistral Medium 3.5 measured
LMArena Vision: creative writingNot measured1198Only 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 GLM 4.5 Air and Mistral Medium 3.5
BenchmarkGLM 4.5 AirMistral Medium 3.5Leader
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

GLM 4.5 Air$0.0008Fits in one request
Mistral Medium 3.5$0.0053Fits in one request

GLM 4.5 Air costs less

Repository review

50K input + 3K output tokens

GLM 4.5 Air$0.013Fits in one request
Mistral Medium 3.5$0.098Fits in one request

GLM 4.5 Air costs less

Agent loop

200K input + 10K output tokens

GLM 4.5 Air$0.051Exceeds the context window
Mistral Medium 3.5$0.375Fits in one request

GLM 4.5 Air 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 GLM 4.5 Air and Mistral Medium 3.5
SpecificationZ.ai GLM 4.5 AirMistral Medium 3.5
MakerZ.aiMistral AI
WeightsOpen weightsNo public weights listed
ReleasedJuly 25, 2025April 30, 2026
Context window131K262K
Input $/Mtok$0.20$1.50
Output $/Mtok$1.10$7.50
Coding indexNot benchmarked25.5
Independent measurements behind it03
Cost per solved taskNot computable$6.02
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 Air better than Mistral Medium 3.5 for coding?

Only Mistral Medium 3.5 has a coding score, 25.5 on the Vibe Coding Index; GLM 4.5 Air has none, so the two cannot be ranked on coding. Pick GLM 4.5 Air for output tokens 6.8x cheaper ($1.10 vs $7.50 per million) and work measured by Kagi LLM Benchmark or Design Arena: websites, where it leads.

Which is cheaper, GLM 4.5 Air or Mistral Medium 3.5?

GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Cost per solved task is known for Mistral Medium 3.5 only.

Which has the bigger context window, GLM 4.5 Air or Mistral Medium 3.5?

Mistral Medium 3.5, with 262K tokens against 131K.

How many benchmarks is the GLM 4.5 Air vs Mistral Medium 3.5 comparison based on?

42 benchmarks have a result for both models as of October 21, 2026. GLM 4.5 Air's coding index rests on 0 independent benchmarks and Mistral Medium 3.5's on 3. Where only one model has a result, the page says so instead of naming a winner.

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