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GLM 5.2 vs Mistral Medium 3.1

GLM 5.2 leads Mistral Medium 3.1 on the Artificial Analysis Intelligence Index, 33.7 to 9.2, and Mistral Medium 3.1 costs 2.2x less per output token ($2.00 vs $4.40 per million). Updated October 21, 2026; 54 benchmarks have a result for both.

Replace GLM 5.2 Replace Mistral Medium 3.1
GLM 5.2Z.ai
Coding
61.1
Overall
62.5
Output $/M
$4.40
54
Mistral Medium 3.1Mistral AI
Coding
No data
Overall
No data
Output $/M
$2.00
0
vs boards won of 54 shared

GLM 5.2 or Mistral Medium 3.1: which to pick

Only GLM 5.2 has a coding score, 61.1 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding.

Pick Mistral Medium 3.1 for output tokens 2.2x cheaper ($2.00 vs $4.40 per million).

Model AGLM 5.2Z.ai61.1/1004 independent benchmarks$0.86 per solved taskModel BMistral Medium 3.1Mistral AINot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
54
GLM 5.2 only
44
Mistral Medium 3.1 only
20
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 5.2 61.1 from 4 benchmarks, Mistral Medium 3.1 not benchmarked.
Widest category
Agentic work, 47.5 points apart on average over 2 shared benchmarks.
Widest single gap
τ²-Bench Telecom: GLM 5.2 99.1% against Mistral Medium 3.1 40.6%, 58.5 points apart on a 0 to 100 scale.
Output price
GLM 5.2 $4.40 against Mistral Medium 3.1 $2.00 per million output tokens, 2.2x apart.
Context window
GLM 5.2 takes 1.05M tokens, Mistral Medium 3.1 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 5.2BarsMistral Medium 3.1Ties
Coding70
Intelligence10
Agentic work20
Reasoning50
Math20
Knowledge80
Web design80
General210
All shared boards540
CodingLike-for-likeSix of these boards feed the Vibe Coding Index70
Coding benchmarks for GLM 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
LMArena WebDev1604Not measuredOnly GLM 5.2 measured
AA Coding Index68.820.5GLM 5.2
LiveCodeBench (Vals AI)69.5%44.8%GLM 5.2
SWE-bench Verified (Vals AI)82.8%Not measuredOnly GLM 5.2 measured
Vibe Code Bench (Vals AI)64.0%Not measuredOnly GLM 5.2 measured
Code migration (Vals AI)37.9%Not measuredOnly GLM 5.2 measured
ProgramBench (Vals AI)0.5%Not measuredOnly GLM 5.2 measured
Terminal-Bench 2.1 (Vals AI)67.8%Not measuredOnly GLM 5.2 measured
SkillsBench (Vals AI)45.1%Not measuredOnly GLM 5.2 measured
LiveCodeBench (Artificial Analysis run)Not measured40.6%Only Mistral Medium 3.1 measured
SciCode51.2%32.4%GLM 5.2
Terminal-Bench Hard (Artificial Analysis run)50.8%10.6%GLM 5.2
FrontierCode24.5%Not measuredOnly GLM 5.2 measured
WeirdML70.1%Not measuredOnly GLM 5.2 measured
ALE-Bench1047.0210.2GLM 5.2
LMArena Text: coding14871433GLM 5.2
LMArena Text: software and IT14861436GLM 5.2
LMArena WebDev: React1617Not measuredOnly GLM 5.2 measured
LMArena WebDev: HTML1565Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for GLM 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
AA Intelligence Index33.79.2GLM 5.2
Epoch Capabilities Index151.9Not measuredOnly GLM 5.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index20
Agentic work benchmarks for GLM 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
AA Agentic Index38.41.9GLM 5.2
Design Arena: agents building web apps1222Not measuredOnly GLM 5.2 measured
Design Arena: agents building full-stack apps1241Not measuredOnly GLM 5.2 measured
Design Arena: agents building mobile apps1160Not measuredOnly GLM 5.2 measured
Design Arena: agents building Android apps1178Not measuredOnly GLM 5.2 measured
Design Arena: agents building Godot games1142Not measuredOnly GLM 5.2 measured
Design Arena: agents building games1206Not measuredOnly GLM 5.2 measured
Design Arena: HTML slides1175Not measuredOnly GLM 5.2 measured
Design Arena: PowerPoint slides1195Not measuredOnly GLM 5.2 measured
SREBench (Vals AI)0.0%Not measuredOnly GLM 5.2 measured
Finance Agent (Vals AI)49.7%Not measuredOnly GLM 5.2 measured
Legal Research Bench (Vals AI)31.3%Not measuredOnly GLM 5.2 measured
Excel Modeling Benchmark (Vals AI)61.5%Not measuredOnly GLM 5.2 measured
τ²-Bench Telecom99.1%40.6%GLM 5.2
APEX-Agents45.2%Not measuredOnly GLM 5.2 measured
PostTrainBench31.7%Not measuredOnly GLM 5.2 measured
Vending-Bench 2$8,314Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for GLM 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
GPQA Diamond85.6%Not measuredOnly GLM 5.2 measured
MMMU Pro (Vals AI)Not measured63.0%Only Mistral Medium 3.1 measured
GPQA Diamond (Artificial Analysis run)89.5%58.8%GLM 5.2
Humanity's Last Exam (Artificial Analysis run)41.1%4.7%GLM 5.2
GPQA Diamond (Epoch AI run)91.9%Not measuredOnly GLM 5.2 measured
ARC-AGI77.0%Not measuredOnly GLM 5.2 measured
ARC-AGI-222.8%Not measuredOnly GLM 5.2 measured
SimpleBench58.8%Not measuredOnly GLM 5.2 measured
Chess puzzles22.0%Not measuredOnly GLM 5.2 measured
Mystery game puzzles19.0%Not measuredOnly GLM 5.2 measured
EBR-bench9.5%Not measuredOnly GLM 5.2 measured
LMArena Text: hard prompts14811426GLM 5.2
LMArena Text: expert14871408GLM 5.2
LMArena Text: hard prompts in English14811435GLM 5.2
LMArena Vision: diagramsNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: homeworkNot measured1165Only Mistral Medium 3.1 measured
Kagi LLM Benchmark62.6%Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for GLM 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
AIMENot measured42.3%Only Mistral Medium 3.1 measured
MATH 500 (Vals AI)Not measured87.0%Only Mistral Medium 3.1 measured
MGSM (Vals AI)Not measured90.9%Only Mistral Medium 3.1 measured
AA Math IndexNot measured38.3Only Mistral Medium 3.1 measured
AIME 2025 (Artificial Analysis run)Not measured38.3%Only Mistral Medium 3.1 measured
OTIS Mock AIME86.4%Not measuredOnly GLM 5.2 measured
FrontierMath, tiers 1 to 359.2%Not measuredOnly GLM 5.2 measured
FrontierMath, tier 429.3%Not measuredOnly GLM 5.2 measured
ProofBench35.0%Not measuredOnly GLM 5.2 measured
LMArena Text: math14831408GLM 5.2
LMArena Text: mathematical work14891412GLM 5.2
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index80
Knowledge benchmarks for GLM 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
MMLU Pro86.7%75.3%GLM 5.2
LegalBench (Vals AI)84.1%62.0%GLM 5.2
CorpFin (Vals AI)66.1%50.7%GLM 5.2
TaxEval (Vals AI)73.3%70.3%GLM 5.2
MortgageTax (Vals AI)Not measured36.5%Only Mistral Medium 3.1 measured
MedQA (Vals AI)Not measured78.2%Only Mistral Medium 3.1 measured
MedCode (Vals AI)40.8%Not measuredOnly GLM 5.2 measured
MMLU Pro (Artificial Analysis run)Not measured68.3%Only Mistral Medium 3.1 measured
SimpleQA Verified34.2%Not measuredOnly GLM 5.2 measured
LMArena Text: science14891444GLM 5.2
LMArena Text: medicine and healthcare14751449GLM 5.2
LMArena Text: legal and government14861439GLM 5.2
LMArena Text: business and finance14511418GLM 5.2
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index80
Web design benchmarks for GLM 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
Design Arena: websites12851133GLM 5.2
Design Arena: UI components12961100GLM 5.2
Design Arena: game dev12681074GLM 5.2
Design Arena: data viz12851144GLM 5.2
Design Arena: 3D12881081GLM 5.2
Design Arena: all code categories12881120GLM 5.2
Design Arena: SVG1214993GLM 5.2
Design Arena: ASCII art1190997GLM 5.2
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index210
General benchmarks for GLM 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
MedScribe (Vals AI)83.5%Not measuredOnly GLM 5.2 measured
IFBench73.3%39.8%GLM 5.2
Long context reasoning (AA-LCR)78.3%42.7%GLM 5.2
DTBench93.6%67.5%GLM 5.2
LMCA45.8%19.1%GLM 5.2
Surface Evolver Bench55.6%Not measuredOnly GLM 5.2 measured
LMArena Text14701424GLM 5.2
LMArena Text: instruction following14661398GLM 5.2
LMArena Text: creative writing14631391GLM 5.2
LMArena VisionNot measured1172Only Mistral Medium 3.1 measured
LMArena Text: English14751438GLM 5.2
LMArena Text: non-English14591408GLM 5.2
LMArena Text: Chinese15221447GLM 5.2
LMArena Text: German14701432GLM 5.2
LMArena Text: Japanese14501379GLM 5.2
LMArena Text: Korean14401380GLM 5.2
LMArena Text: French14791460GLM 5.2
LMArena Text: Spanish14781433GLM 5.2
LMArena Text: Russian14681411GLM 5.2
LMArena Text: Polish14561430GLM 5.2
LMArena Text: multi-turn14691418GLM 5.2
LMArena Text: longer queries14801406GLM 5.2
LMArena Text: writing and language14631395GLM 5.2
LMArena Text: entertainment and media14501390GLM 5.2
LMArena Vision: EnglishNot measured1179Only Mistral Medium 3.1 measured
LMArena Vision: ChineseNot measured1190Only Mistral Medium 3.1 measured
LMArena Vision: reading textNot measured1175Only Mistral Medium 3.1 measured
LMArena Vision: humorNot measured1168Only Mistral Medium 3.1 measured
LMArena Vision: captioningNot measured1145Only Mistral Medium 3.1 measured
LMArena Vision: recognizing thingsNot measured1147Only Mistral Medium 3.1 measured
LMArena Vision: creative writingNot measured1200Only Mistral Medium 3.1 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 5.2 and Mistral Medium 3.1
BenchmarkGLM 5.2Mistral Medium 3.1Leader
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 5.2$0.0036Fits in one request
Mistral Medium 3.1$0.0014Fits in one request

Mistral Medium 3.1 costs less

Repository review

50K input + 3K output tokens

GLM 5.2$0.083Fits in one request
Mistral Medium 3.1$0.026Fits in one request

Mistral Medium 3.1 costs less

Agent loop

200K input + 10K output tokens

GLM 5.2$0.324Fits in one request
Mistral Medium 3.1$0.100Exceeds the context window

Mistral Medium 3.1 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 5.2 and Mistral Medium 3.1
SpecificationZ.ai GLM 5.2Mistral Medium 3.1
MakerZ.aiMistral AI
WeightsOpen weightsNo public weights listed
ReleasedJune 16, 2026August 13, 2025
Context window1.05M131K
Input $/Mtok$1.40$0.40
Output $/Mtok$4.40$2.00
Coding index61.1Not benchmarked
Independent measurements behind it40
Cost per solved task$0.86Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.2 better than Mistral Medium 3.1 for coding?

Only GLM 5.2 has a coding score, 61.1 on the Vibe Coding Index; Mistral Medium 3.1 has none, so the two cannot be ranked on coding. Pick Mistral Medium 3.1 for output tokens 2.2x cheaper ($2.00 vs $4.40 per million).

Which is cheaper, GLM 5.2 or Mistral Medium 3.1?

GLM 5.2 costs $1.40 per million input tokens and $4.40 per million output tokens; Mistral Medium 3.1 costs $0.40 and $2.00. Cost per solved task is known for GLM 5.2 only.

Which has the bigger context window, GLM 5.2 or Mistral Medium 3.1?

GLM 5.2, with 1.05M tokens against 131K.

How many benchmarks is the GLM 5.2 vs Mistral Medium 3.1 comparison based on?

54 benchmarks have a result for both models as of October 21, 2026. GLM 5.2's coding index rests on 4 independent benchmarks and Mistral Medium 3.1's on 0. Where only one model has a result, the page says so instead of naming a winner.

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