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GLM 4.5 Air vs Mistral Large 2407

GLM 4.5 Air leads Mistral Large 2407 on the Artificial Analysis Intelligence Index, 11.1 to 7.6, and GLM 4.5 Air costs 5.5x less per output token ($1.10 vs $6.00 per million). Updated October 22, 2026; 10 benchmarks have a result for both.

GLM 4.5 AirZ.ai
Coding
No data
Overall
No data
Output $/M
$1.10
10
Mistral Large 2407Mistral AI
Coding
No data
Overall
No data
Output $/M
$6.00
0
vs boards won of 10 shared

GLM 4.5 Air or Mistral Large 2407: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GLM 4.5 Air for output tokens 5.5x cheaper ($1.10 vs $6.00 per million).

Shared results
10
GLM 4.5 Air only
38
Mistral Large 2407 only
7
Like-for-like categories
7 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 Large 2407 not benchmarked.
Widest category
Math, 80.7 points apart on average over 2 shared benchmarks.
Widest single gap
AA Math Index: GLM 4.5 Air 80.7 against Mistral Large 2407 0.0, 80.7 points apart on a 0 to 100 scale.
Output price
GLM 4.5 Air $1.10 against Mistral Large 2407 $6.00 per million output tokens, 5.5x apart.
Context window
Both take 131K 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
CategoryGLM 4.5 AirBarsMistral Large 2407Ties
Coding10
Intelligence10
Agentic work10
Reasoning20
Math20
Knowledge10
General20
All shared boards100
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for GLM 4.5 Air and Mistral Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
LiveCodeBench (Artificial Analysis run)68.4%26.7%GLM 4.5 Air
Terminal-Bench Hard (Artificial Analysis run)20.5%Not measuredOnly GLM 4.5 Air measured
GSO-Bench2.9%Not measuredOnly GLM 4.5 Air measured
LMArena Text: coding1397Not measuredOnly GLM 4.5 Air measured
LMArena Text: software and IT1401Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 34 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.5 Air and Mistral Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
AA Intelligence Index11.17.6GLM 4.5 Air
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for GLM 4.5 Air and Mistral Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
τ²-Bench Telecom46.5%33.0%GLM 4.5 Air
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for GLM 4.5 Air and Mistral Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
GPQA Diamond (Artificial Analysis run)73.3%47.2%GLM 4.5 Air
Humanity's Last Exam (Artificial Analysis run)7.0%2.9%GLM 4.5 Air
GPQA Diamond (Epoch AI run)Not measured49.0%Only Mistral Large 2407 measured
SimpleBenchNot measured22.5%Only Mistral Large 2407 measured
LMArena Text: hard prompts1379Not measuredOnly GLM 4.5 Air measured
LMArena Text: expert1370Not measuredOnly GLM 4.5 Air measured
LMArena Text: hard prompts in English1388Not measuredOnly GLM 4.5 Air measured
Kagi LLM Benchmark43.0%Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GLM 4.5 Air and Mistral Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
AA Math Index80.70.0GLM 4.5 Air
AIME 2025 (Artificial Analysis run)80.7%0.0%GLM 4.5 Air
OTIS Mock AIMENot measured8.5%Only Mistral Large 2407 measured
MATH level 5Not measured44.8%Only Mistral Large 2407 measured
LMArena Text: math1396Not measuredOnly GLM 4.5 Air measured
LMArena Text: mathematical work1396Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for GLM 4.5 Air and Mistral Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
MMLU Pro (Artificial Analysis run)81.5%68.3%GLM 4.5 Air
MMLUNot measured80.0%Only Mistral Large 2407 measured
LMArena Text: science1407Not measuredOnly GLM 4.5 Air measured
LMArena Text: medicine and healthcare1402Not measuredOnly GLM 4.5 Air measured
LMArena Text: legal and government1382Not measuredOnly GLM 4.5 Air measured
LMArena Text: business and finance1371Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 12 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared
Web design benchmarks for GLM 4.5 Air and Mistral Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
Design Arena: websites1146Not measuredOnly GLM 4.5 Air measured
Design Arena: UI components1120Not measuredOnly GLM 4.5 Air measured
Design Arena: game dev1094Not measuredOnly GLM 4.5 Air measured
Design Arena: data viz1186Not measuredOnly GLM 4.5 Air measured
Design Arena: 3D1122Not measuredOnly GLM 4.5 Air measured
Design Arena: all code categories1137Not measuredOnly GLM 4.5 Air measured
Design Arena: SVG1071Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 2 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index20
General benchmarks for GLM 4.5 Air and Mistral Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
IFBench37.6%31.6%GLM 4.5 Air
Long context reasoning (AA-LCR)46.7%2.0%GLM 4.5 Air
DTBenchNot measured61.2%Only Mistral Large 2407 measured
Creative writing (Lech Mazur)Not measured69.0%Only Mistral Large 2407 measured
LMArena Text1384Not measuredOnly GLM 4.5 Air measured
LMArena Text: instruction following1354Not measuredOnly GLM 4.5 Air measured
LMArena Text: creative writing1343Not measuredOnly GLM 4.5 Air measured
LMArena Text: English1397Not measuredOnly GLM 4.5 Air measured
LMArena Text: non-English1366Not measuredOnly GLM 4.5 Air measured
LMArena Text: Chinese1426Not measuredOnly GLM 4.5 Air measured
LMArena Text: German1377Not measuredOnly GLM 4.5 Air measured
LMArena Text: Japanese1348Not measuredOnly GLM 4.5 Air measured
LMArena Text: Korean1308Not measuredOnly GLM 4.5 Air measured
LMArena Text: French1400Not measuredOnly GLM 4.5 Air measured
LMArena Text: Spanish1385Not measuredOnly GLM 4.5 Air measured
LMArena Text: Russian1373Not measuredOnly GLM 4.5 Air measured
LMArena Text: Polish1368Not measuredOnly GLM 4.5 Air measured
LMArena Text: multi-turn1371Not measuredOnly GLM 4.5 Air measured
LMArena Text: longer queries1366Not measuredOnly GLM 4.5 Air measured
LMArena Text: writing and language1354Not measuredOnly GLM 4.5 Air measured
LMArena Text: entertainment and media1339Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 25 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 Large 2407
BenchmarkGLM 4.5 AirMistral Large 2407Leader
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 Large 2407$0.0050Fits 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 Large 2407$0.118Fits 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 Large 2407$0.460Exceeds the context window

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 Large 2407
SpecificationZ.ai GLM 4.5 AirMistral Large 2407
MakerZ.aiMistral AI
WeightsOpen weightsNo public weights listed
ReleasedJuly 25, 2025November 19, 2024
Context window131K131K
Input $/Mtok$0.20$2.00
Output $/Mtok$1.10$6.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5 Air better than Mistral Large 2407 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5 Air for output tokens 5.5x cheaper ($1.10 vs $6.00 per million).

Which is cheaper, GLM 4.5 Air or Mistral Large 2407?

GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; Mistral Large 2407 costs $2.00 and $6.00. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.5 Air or Mistral Large 2407?

Neither: both take 131K tokens.

How many benchmarks is the GLM 4.5 Air vs Mistral Large 2407 comparison based on?

10 benchmarks have a result for both models as of October 22, 2026. GLM 4.5 Air's coding index rests on 0 independent benchmarks and Mistral Large 2407's on 0. Where only one model has a result, the page says so instead of naming a winner.

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