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GLM 5.1 vs Mistral Medium 3.5

Updated October 21, 2026. 64 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 5.1 Replace Mistral Medium 3.5
GLM 5.1Z.ai
Coding
44.0
Overall
26.1
Output $/M
$4.40
64
Mistral Medium 3.5Mistral AI
Coding
9.2
Overall
14.2
Output $/M
$7.50
0
vs boards won of 64 shared

Decision reading

Pick GLM 5.1 for coding: it scores 44.0 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5.

Pick Mistral Medium 3.5 when the context window is larger, 262K against 205K tokens.

Model AGLM 5.1Z.ai44.0/1001 independent benchmark$0.60 per solved taskModel BMistral Medium 3.5Mistral AI9.2/1001 independent benchmark$6.02 per solved task
Shared results
64
GLM 5.1 only
25
Mistral Medium 3.5 only
16
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 5.1 44.0 from 1 benchmark, Mistral Medium 3.5 9.2 from 1 benchmark.
Widest category
Web design, 24.4 points apart on average over 8 shared benchmarks.
Widest single gap
GPQA Diamond: GLM 5.1 84.5% against Mistral Medium 3.5 34.9%, 49.7 points apart on a 0 to 100 scale.
Output price
GLM 5.1 $4.40 against Mistral Medium 3.5 $7.50 per million output tokens, 1.7x apart.
Context window
GLM 5.1 takes 205K 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 5.1BarsMistral Medium 3.5Ties
Coding130
Intelligence20
Agentic work40
Reasoning60
Math30
Knowledge90
Web design80
General190
All shared boards640
CodingLike-for-likeFour of these boards feed the Vibe Coding Index130
Coding benchmarks for GLM 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral Medium 3.5Leader
LMArena WebDev15081264GLM 5.1
AA Coding Index55.846.9GLM 5.1
LiveCodeBench (Vals AI)81.4%Not measuredOnly GLM 5.1 measured
SWE-bench Verified (Vals AI)76.4%66.4%GLM 5.1
Vibe Code Bench (Vals AI)31.5%2.9%GLM 5.1
Code migration (Vals AI)25.8%5.1%GLM 5.1
ProgramBench (Vals AI)0.0%Not measuredOnly GLM 5.1 measured
Terminal-Bench 2.1 (Vals AI)56.9%39.0%GLM 5.1
SciCode44.8%40.2%GLM 5.1
Terminal-Bench Hard (Artificial Analysis run)43.2%33.3%GLM 5.1
WeirdML57.1%Not measuredOnly GLM 5.1 measured
ALE-Bench887.1764.0GLM 5.1
LMArena Text: coding14851460GLM 5.1
LMArena Text: software and IT14841458GLM 5.1
LMArena WebDev: React15051254GLM 5.1
LMArena WebDev: HTML15081308GLM 5.1
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for GLM 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral Medium 3.5Leader
AA Intelligence Index26.114.2GLM 5.1
Epoch Capabilities Index149.8141.4GLM 5.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index40
Agentic work benchmarks for GLM 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral Medium 3.5Leader
AA Agentic Index23.97.0GLM 5.1
Design Arena: agents building web apps1175Not measuredOnly GLM 5.1 measured
Design Arena: agents building full-stack apps1167Not measuredOnly GLM 5.1 measured
Design Arena: agents building mobile apps1162Not measuredOnly GLM 5.1 measured
Design Arena: agents building Android apps1186Not measuredOnly GLM 5.1 measured
Design Arena: agents building Godot games1053Not measuredOnly GLM 5.1 measured
Design Arena: agents building games1164Not measuredOnly GLM 5.1 measured
Design Arena: HTML slides1170Not measuredOnly GLM 5.1 measured
Design Arena: PowerPoint slides1189Not measuredOnly GLM 5.1 measured
Design Arena: spreadsheets1315Not measuredOnly GLM 5.1 measured
Finance Agent (Vals AI)44.8%32.1%GLM 5.1
Tax Agent Bench (Vals AI)Not measured4.5%Only Mistral Medium 3.5 measured
Legal Research Bench (Vals AI)27.9%9.1%GLM 5.1
Excel Modeling Benchmark (Vals AI)Not measured11.2%Only Mistral Medium 3.5 measured
τ²-Bench Telecom97.7%94.2%GLM 5.1
APEX-Agents40.9%Not measuredOnly GLM 5.1 measured
Vending-Bench 2$5,634Not measuredOnly GLM 5.1 measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index60
Reasoning benchmarks for GLM 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral Medium 3.5Leader
GPQA Diamond84.5%34.9%GLM 5.1
GPQA Diamond (Artificial Analysis run)86.8%74.8%GLM 5.1
Humanity's Last Exam (Artificial Analysis run)30.1%13.8%GLM 5.1
GPQA Diamond (Epoch AI run)89.9%Not measuredOnly GLM 5.1 measured
SimpleBench55.1%Not measuredOnly GLM 5.1 measured
Chess puzzles20.0%Not measuredOnly GLM 5.1 measured
LMArena Text: hard prompts14731436GLM 5.1
LMArena Text: expert14781432GLM 5.1
LMArena Text: hard prompts in English14821445GLM 5.1
LMArena Vision: diagramsNot measured1254Only Mistral Medium 3.5 measured
LMArena Vision: homeworkNot measured1230Only Mistral Medium 3.5 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for GLM 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral Medium 3.5Leader
AIME91.9%Not measuredOnly GLM 5.1 measured
OTIS Mock AIME93.3%Not measuredOnly GLM 5.1 measured
FrontierMath, tiers 1 to 336.8%Not measuredOnly GLM 5.1 measured
ProofBench22.2%9.0%GLM 5.1
LMArena Text: math14731431GLM 5.1
LMArena Text: mathematical work14701440GLM 5.1
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index90
Knowledge benchmarks for GLM 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral Medium 3.5Leader
MMLU Pro86.9%75.3%GLM 5.1
LegalBench (Vals AI)84.4%Not measuredOnly GLM 5.1 measured
CaseLaw (Vals AI)51.5%44.2%GLM 5.1
CorpFin (Vals AI)64.5%58.8%GLM 5.1
TaxEval (Vals AI)71.2%68.0%GLM 5.1
MortgageTax (Vals AI)Not measured28.9%Only Mistral Medium 3.5 measured
MedCode (Vals AI)41.6%33.8%GLM 5.1
SimpleQA Verified34.0%Not measuredOnly GLM 5.1 measured
LMArena Text: science14781428GLM 5.1
LMArena Text: medicine and healthcare14741409GLM 5.1
LMArena Text: legal and government14651437GLM 5.1
LMArena Text: business and finance14521426GLM 5.1
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 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral Medium 3.5Leader
Design Arena: websites12901142GLM 5.1
Design Arena: UI components12921079GLM 5.1
Design Arena: game dev12651079GLM 5.1
Design Arena: data viz13661120GLM 5.1
Design Arena: 3D13361061GLM 5.1
Design Arena: all code categories12681122GLM 5.1
Design Arena: SVG1217949GLM 5.1
Design Arena: ASCII art11421062GLM 5.1
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index190
General benchmarks for GLM 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral Medium 3.5Leader
Public Benefits Bench (Vals AI)61.8%Not measuredOnly GLM 5.1 measured
SAGE (Vals AI)Not measured37.6%Only Mistral Medium 3.5 measured
MedScribe (Vals AI)72.3%67.7%GLM 5.1
Vals Multimodal IndexNot measured34.8%Only Mistral Medium 3.5 measured
IFBench76.3%68.8%GLM 5.1
Long context reasoning (AA-LCR)73.7%69.3%GLM 5.1
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
ExploitBench18.1%Not measuredOnly GLM 5.1 measured
LMArena Text14631421GLM 5.1
LMArena Text: instruction following14531415GLM 5.1
LMArena Text: creative writing14531374GLM 5.1
LMArena VisionNot measured1222Only Mistral Medium 3.5 measured
LMArena Text: English14761433GLM 5.1
LMArena Text: non-English14481404GLM 5.1
LMArena Text: Chinese15151444GLM 5.1
LMArena Text: German14671453GLM 5.1
LMArena Text: Japanese1435Not measuredOnly GLM 5.1 measured
LMArena Text: Korean14241384GLM 5.1
LMArena Text: French14701448GLM 5.1
LMArena Text: Spanish14681411GLM 5.1
LMArena Text: Russian14541395GLM 5.1
LMArena Text: Polish14491430GLM 5.1
LMArena Text: multi-turn14731423GLM 5.1
LMArena Text: longer queries14671415GLM 5.1
LMArena Text: writing and language14541384GLM 5.1
LMArena Text: entertainment and media14421382GLM 5.1
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 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.1 and Mistral Medium 3.5
BenchmarkGLM 5.1Mistral 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 5.1$0.0036Fits in one request
Mistral Medium 3.5$0.0053Fits in one request

GLM 5.1 costs less

Repository review

50K input + 3K output tokens

GLM 5.1$0.083Fits in one request
Mistral Medium 3.5$0.098Fits in one request

GLM 5.1 costs less

Agent loop

200K input + 10K output tokens

GLM 5.1$0.324Exceeds the context window
Mistral Medium 3.5$0.375Fits in one request

GLM 5.1 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 5.1 and Mistral Medium 3.5
SpecificationZ.ai GLM 5.1Mistral Medium 3.5
MakerZ.aiMistral AI
WeightsOpen weightsNo public weights listed
ReleasedApril 7, 2026April 30, 2026
Context window205K262K
Input $/Mtok$1.40$1.50
Output $/Mtok$4.40$7.50
Coding index44.09.2
Independent measurements behind it11
Cost per solved task$0.60$6.02
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.1 better than Mistral Medium 3.5 for coding?

Pick GLM 5.1 for coding: it scores 44.0 on the Vibe Coding Index against 9.2 for Mistral Medium 3.5. Pick Mistral Medium 3.5 when the context window is larger, 262K against 205K tokens.

Which is cheaper, GLM 5.1 or Mistral Medium 3.5?

GLM 5.1 costs $1.40 per million input tokens and $4.40 per million output tokens; Mistral Medium 3.5 costs $1.50 and $7.50. Per solved SWE-bench Verified task, GLM 5.1 costs $0.60 and Mistral Medium 3.5 $6.02.

Which has the bigger context window, GLM 5.1 or Mistral Medium 3.5?

Mistral Medium 3.5, with 262K tokens against 205K.

How many benchmarks is the GLM 5.1 vs Mistral Medium 3.5 comparison based on?

64 benchmarks have a result for both models as of October 21, 2026. GLM 5.1's coding index rests on 1 independent benchmark and Mistral Medium 3.5's on 1. Where only one model has a result, the page says so instead of naming a winner.

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