Noometry

Model comparison

GLM-4.7 vs Mistral Medium 3.5

GLM-4.7 is the stronger model overall, scoring 42.0 to 40.2 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Mistral Medium 3.5 Mistral AI

40.2

Rank #152 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.7 scores higher in 5 categories and Mistral Medium 3.5 in 3 categories; 4 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GLM-4.7 leads 44.0 to 36.0.
  • GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.50 / $7.50 for Mistral Medium 3.5.
  • Mistral Medium 3.5 accepts more context: 262K tokens versus 205K.

Side by side

GLM-4.7Mistral Medium 3.5
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index42.040.2
Released2025-12-22—
WeightsOpenOpen
Context window205K262K
Max output131K210K
Input $ / M tokens$0.60$1.50
Output $ / M tokens$2.20$7.50
Results tracked3622

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), Mistral Medium 3.5: 36.0 (#213)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena WebDev14351264
LMArena Coding14541461
SciCode45.1%—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.5 (#103), Mistral Medium 3.5: —

BenchmarkGLM-4.7Mistral Medium 3.5
Terminal-Bench33.4%—
Vending-Bench 22,377—

Reasoning GLM-4.7 leads

GLM-4.7: 24.3 (#164), Mistral Medium 3.5: 17.3 (#295)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Hard Prompts14431436
Epoch Capabilities Index143.51141.35
SimpleBench47.7%—
Kagi LLM Benchmark—41.4%
NYT Connections (extended)—12.9%
CritPt1.7%—
Chess Puzzles6%—

Math Too close to call

GLM-4.7: 38.6 (#135), Mistral Medium 3.5: 39.1 (#113)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Math14231431
OTIS Mock AIME 2024-202583.3%—
ProofBench6%—
FrontierMath (Feb 2025 set)2.4%—
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), Mistral Medium 3.5: 40.0 (#126)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Expert14241432
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multimodal Not comparable

GLM-4.7: —, Mistral Medium 3.5: 38.3 (#65)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Vision—1223

Multilingual Too close to call

GLM-4.7: 52.8 (#79), Mistral Medium 3.5: 51.9 (#100)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Non-English14171404
LMArena Chinese14951442
LMArena French14321448
LMArena German14241451
LMArena Korean13991385
LMArena Russian14231395
LMArena Spanish14341409
LMArena Japanese1439—

Instruction Following Too close to call

GLM-4.7: 74.4 (#95), Mistral Medium 3.5: 74.6 (#90)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Instruction Following14111415

Long Context Too close to call

GLM-4.7: 42.8 (#116), Mistral Medium 3.5: 43.2 (#103)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Longer Query14321415
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 60.9 (#93), Mistral Medium 3.5: 58.5 (#117)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Text14351421
LMArena Creative Writing14011374
LMArena Multi-Turn14461423
EQ-Bench Creative Writing1413—
EQ-Bench 4—993

Frequently asked questions

Is GLM-4.7 better than Mistral Medium 3.5?

GLM-4.7 is the stronger model overall, scoring 42.0 to 40.2 on the Noometry Index.

Which is cheaper, GLM-4.7 or Mistral Medium 3.5?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Mistral Medium 3.5 lists at $1.50 and $7.50.

Is GLM-4.7 or Mistral Medium 3.5 better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 36.0 in the Noometry coding category.

Which has the bigger context window?

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

How many benchmarks do GLM-4.7 and Mistral Medium 3.5 share?

18 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Mistral Medium 3.5 has 22.

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