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GLM 4.5 Air vs Mixtral 8x22B Instruct

GLM 4.5 Air leads Mixtral 8x22B Instruct on the Artificial Analysis Intelligence Index, 11.1 to 5.7, and GLM 4.5 Air costs 5.5x less per output token ($1.10 vs $6.00 per million). Updated October 21, 2026; 5 benchmarks have a result for both.

GLM 4.5 AirZ.ai
Coding
No data
Overall
11.1
Output $/M
$1.10
5
Mixtral 8x22B InstructMistral AI
Coding
No data
Overall
5.7
Output $/M
$6.00
0
vs boards won of 5 shared

GLM 4.5 Air or Mixtral 8x22B Instruct: 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) and a larger context window (131K against 66K tokens).

Shared results
5
GLM 4.5 Air only
42
Mixtral 8x22B Instruct only
2
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
GLM 4.5 Air not benchmarked, Mixtral 8x22B Instruct not benchmarked.
Widest category
Coding, 53.6 points apart on average over 1 shared benchmark.
Widest single gap
LiveCodeBench (Artificial Analysis run): GLM 4.5 Air 68.4% against Mixtral 8x22B Instruct 14.8%, 53.6 points apart on a 0 to 100 scale.
Output price
GLM 4.5 Air $1.10 against Mixtral 8x22B Instruct $6.00 per million output tokens, 5.5x apart.
Context window
GLM 4.5 Air takes 131K tokens, Mixtral 8x22B Instruct 66K.

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 AirBarsMixtral 8x22B InstructTies
Coding10
Intelligence10
Reasoning20
Knowledge10
All shared boards50
CodingLike-for-likeSix of these boards feed the Vibe Coding Index10
Coding benchmarks for GLM 4.5 Air and Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
LiveCodeBench (Artificial Analysis run)68.4%14.8%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 33 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 4.5 Air and Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
AA Intelligence Index11.15.7GLM 4.5 Air
Epoch Capabilities IndexNot measured122.0Only Mixtral 8x22B Instruct measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
Agentic work benchmarks for GLM 4.5 Air and Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
τ²-Bench Telecom46.5%Not measuredOnly GLM 4.5 Air measured
Neither model has a result on the other 38 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index20
Reasoning benchmarks for GLM 4.5 Air and Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
GPQA Diamond (Artificial Analysis run)73.3%33.2%GLM 4.5 Air
Humanity's Last Exam (Artificial Analysis run)7.0%4.0%GLM 4.5 Air
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
Neither model has a result on the other 16 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for GLM 4.5 Air and Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
AA Math Index80.7Not measuredOnly GLM 4.5 Air measured
AIME 2025 (Artificial Analysis run)80.7%Not measuredOnly GLM 4.5 Air 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 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index10
Knowledge benchmarks for GLM 4.5 Air and Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
MMLU Pro (Artificial Analysis run)81.5%53.7%GLM 4.5 Air
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 Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
Design Arena: websites1146Not measuredOnly GLM 4.5 Air measured
Design Arena: UI components1123Not 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: 3D1123Not 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
GeneralDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
General benchmarks for GLM 4.5 Air and Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
IFBench37.6%Not measuredOnly GLM 4.5 Air measured
Long context reasoning (AA-LCR)46.7%Not measuredOnly GLM 4.5 Air measured
DTBenchNot measured55.1%Only Mixtral 8x22B Instruct 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 26 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 Mixtral 8x22B Instruct
BenchmarkGLM 4.5 AirMixtral 8x22B InstructLeader
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
Mixtral 8x22B Instruct$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
Mixtral 8x22B Instruct$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
Mixtral 8x22B Instruct$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 Mixtral 8x22B Instruct
SpecificationZ.ai GLM 4.5 AirMistral Mixtral 8x22B Instruct
MakerZ.aiMistral AI
WeightsOpen weightsOpen weights
ReleasedJuly 25, 2025April 17, 2024
Context window131K66K
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 Mixtral 8x22B Instruct 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) and a larger context window (131K against 66K tokens).

Which is cheaper, GLM 4.5 Air or Mixtral 8x22B Instruct?

GLM 4.5 Air costs $0.20 per million input tokens and $1.10 per million output tokens; Mixtral 8x22B Instruct 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 Mixtral 8x22B Instruct?

GLM 4.5 Air, with 131K tokens against 66K.

How many benchmarks is the GLM 4.5 Air vs Mixtral 8x22B Instruct comparison based on?

5 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 Mixtral 8x22B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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