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GLM 4.5V vs Mistral Medium 3

Mistral Medium 3 leads GLM 4.5V on the Artificial Analysis Intelligence Index, 9.0 to 7.6, at about the same output price ($2.00 vs $1.80 per million). Updated October 21, 2026; 40 benchmarks have a result for both.

Replace GLM 4.5V Replace Mistral Medium 3
GLM 4.5VZ.ai
Coding
No data
Overall
No data
Output $/M
$1.80
10
Mistral Medium 3Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
30
vs boards won of 40 shared

GLM 4.5V or Mistral Medium 3: which to pick

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

Pick GLM 4.5V for output tokens 1.1x cheaper ($1.80 vs $2.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AGLM 4.5VZ.aiNot benchmarkedNo coding benchmarkNo cost per solved taskModel BMistral Medium 3Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
40
GLM 4.5V only
1
Mistral Medium 3 only
17
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 4.5V not benchmarked, Mistral Medium 3 not benchmarked.
Widest category
Math, 22.1 points apart on average over 4 shared benchmarks.
Widest single gap
AA Math Index: GLM 4.5V 73.0 against Mistral Medium 3 30.3, 42.7 points apart on a 0 to 100 scale.
Output price
GLM 4.5V $1.80 against Mistral Medium 3 $2.00 per million output tokens, 1.1x apart.
Context window
GLM 4.5V takes 66K tokens, Mistral Medium 3 131K.

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 4.5VBarsMistral Medium 3Ties
Coding22
Intelligence01
Agentic work01
Reasoning34
Math31
Knowledge14
General117
All shared boards1030
CodingLike-for-likeSix of these boards feed the Vibe Coding Index22
Coding benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
LiveCodeBench (Artificial Analysis run)60.4%40.0%GLM 4.5V
Terminal-Bench Hard (Artificial Analysis run)6.8%3.8%GLM 4.5V
LMArena Text: coding13471385Mistral Medium 3
LMArena Text: software and IT13531385Mistral Medium 3
Neither model has a result on the other 35 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
AA Intelligence Index7.69.0Mistral Medium 3
Epoch Capabilities IndexNot measured134.0Only Mistral Medium 3 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
τ²-Bench Telecom22.5%24.3%Mistral Medium 3
Neither model has a result on the other 40 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index34
Reasoning benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
GPQA Diamond (Artificial Analysis run)68.4%57.8%GLM 4.5V
Humanity's Last Exam (Artificial Analysis run)6.3%4.1%GLM 4.5V
LMArena Text: hard prompts13351364Mistral Medium 3
LMArena Text: expert13531342GLM 4.5V
LMArena Text: hard prompts in English13571374Mistral Medium 3
LMArena Vision: diagrams11511155Mistral Medium 3
LMArena Vision: homework11631165Mistral Medium 3
Kagi LLM Benchmark59.8%Not measuredOnly GLM 4.5V measured
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index31
Math benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
AA Math Index73.030.3GLM 4.5V
AIME 2025 (Artificial Analysis run)73.0%30.3%GLM 4.5V
LMArena Text: math13541353GLM 4.5V
LMArena Text: mathematical work13361354Mistral Medium 3
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index14
Knowledge benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
MMLU Pro (Artificial Analysis run)78.8%76.0%GLM 4.5V
LMArena Text: science13301381Mistral Medium 3
LMArena Text: medicine and healthcare13491381Mistral Medium 3
LMArena Text: legal and government13381384Mistral Medium 3
LMArena Text: business and finance13091352Mistral Medium 3
Neither model has a result on the other 13 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
Web design benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
Design Arena: websitesNot measured1079Only Mistral Medium 3 measured
Design Arena: UI componentsNot measured1024Only Mistral Medium 3 measured
Design Arena: game devNot measured1018Only Mistral Medium 3 measured
Design Arena: data vizNot measured1034Only Mistral Medium 3 measured
Design Arena: 3DNot measured1084Only Mistral Medium 3 measured
Design Arena: all code categoriesNot measured1069Only Mistral Medium 3 measured
Neither model has a result on the other 3 boards here
GeneralLike-for-likePublic boards, shown as published, kept out of the index117
General benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
IFBench34.2%39.3%Mistral Medium 3
Long context reasoning (AA-LCR)0.0%31.3%Mistral Medium 3
DTBenchNot measured62.3%Only Mistral Medium 3 measured
LMArena Text13331370Mistral Medium 3
LMArena Text: instruction following13111338Mistral Medium 3
LMArena Text: creative writing12941343Mistral Medium 3
LMArena Vision11541157Mistral Medium 3
LMArena Text: English13621385Mistral Medium 3
LMArena Text: non-English13031353Mistral Medium 3
LMArena Text: Chinese13371374Mistral Medium 3
LMArena Text: GermanNot measured1377Only Mistral Medium 3 measured
LMArena Text: JapaneseNot measured1316Only Mistral Medium 3 measured
LMArena Text: KoreanNot measured1304Only Mistral Medium 3 measured
LMArena Text: FrenchNot measured1368Only Mistral Medium 3 measured
LMArena Text: Spanish13361364Mistral Medium 3
LMArena Text: Russian12981359Mistral Medium 3
LMArena Text: Polish13021371Mistral Medium 3
LMArena Text: multi-turn13331384Mistral Medium 3
LMArena Text: longer queries13051360Mistral Medium 3
LMArena Text: writing and language13021352Mistral Medium 3
LMArena Text: entertainment and media13031335Mistral Medium 3
LMArena Vision: English11831172GLM 4.5V
LMArena Vision: ChineseNot measured1161Only Mistral Medium 3 measured
LMArena Vision: reading text11511154Mistral Medium 3
LMArena Vision: humorNot measured1145Only Mistral Medium 3 measured
LMArena Vision: captioningNot measured1094Only Mistral Medium 3 measured
LMArena Vision: recognizing thingsNot measured1141Only Mistral Medium 3 measured
LMArena Vision: creative writingNot measured1146Only Mistral Medium 3 measured
Neither model has a result on the other 18 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.5V and Mistral Medium 3
BenchmarkGLM 4.5VMistral Medium 3Leader
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 4.5V$0.0015Fits in one request
Mistral Medium 3$0.0014Fits in one request

Mistral Medium 3 costs less

Repository review

50K input + 3K output tokens

GLM 4.5V$0.035Fits in one request
Mistral Medium 3$0.026Fits in one request

Mistral Medium 3 costs less

Agent loop

200K input + 10K output tokens

GLM 4.5V$0.138Exceeds the context window
Mistral Medium 3$0.100Exceeds the context window

Mistral Medium 3 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 4.5V and Mistral Medium 3
SpecificationZ.ai GLM 4.5VMistral Medium 3
MakerZ.aiMistral AI
WeightsOpen weightsNo public weights listed
ReleasedAugust 11, 2025May 7, 2025
Context window66K131K
Input $/Mtok$0.60$0.40
Output $/Mtok$1.80$2.00
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5V better than Mistral Medium 3 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GLM 4.5V for output tokens 1.1x cheaper ($1.80 vs $2.00 per million) and work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, GLM 4.5V or Mistral Medium 3?

GLM 4.5V costs $0.60 per million input tokens and $1.80 per million output tokens; Mistral Medium 3 costs $0.40 and $2.00. Cost per solved task is known for neither of them.

Which has the bigger context window, GLM 4.5V or Mistral Medium 3?

Mistral Medium 3, with 131K tokens against 66K.

How many benchmarks is the GLM 4.5V vs Mistral Medium 3 comparison based on?

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

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