Noometry

Model comparison

GLM-4.7 vs Mistral Medium 3.5

GLM-4.7 is the stronger model overall, scoring 41.7 to 39.6 on the Noometry Index.

Last verified . 18 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

41.7

Rank #117 Confirmed

Mistral Medium 3.5 Mistral AI

39.6

Rank #151 Confirmed

Summary

  • They share 18 benchmarks with published results for both. GLM-4.7 scores higher in 6 categories and Mistral Medium 3.5 in 2 categories; 5 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GLM-4.7 leads 43.6 to 35.7.
  • 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 Index41.739.6
Released2025-12-22—
WeightsOpenOpen
Context window205K262K
Max output131K210K
Input $ / M tokens$0.60$1.50
Output $ / M tokens$2.20$7.50
Results tracked3622

Sponsored placements are available on pages like this one. Advertise on Noometry

Category by category

Coding GLM-4.7 leads

GLM-4.7: 43.6 (#74), Mistral Medium 3.5: 35.7 (#208)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena WebDev14351263
LMArena Coding14541461
SciCode45.1%—
ALE-Bench399.48—

Agentic & Tool Use Not comparable

GLM-4.7: 26.4 (#96), 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: 23.7 (#161), Mistral Medium 3.5: 16.6 (#290)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Hard Prompts14431436
Epoch Capabilities Index143.53141.42
SimpleBench47.7%—
Kagi LLM Benchmark—41.4%
NYT Connections (extended)—12.9%
CritPt1.7%—
Chess Puzzles6%—

Math GLM-4.7 leads

GLM-4.7: 37.7 (#92), Mistral Medium 3.5: 36.4 (#113)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Math14231432
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 (#74), Mistral Medium 3.5: 39.3 (#123)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Expert14241431
GPQA Diamond83.3%—
SimpleQA Verified32.2%—
Vectara Hallucination Rate11.7%—

Multimodal Not comparable

GLM-4.7: —, Mistral Medium 3.5: 37.6 (#64)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Vision—1222

Multilingual Too close to call

GLM-4.7: 53.0 (#75), Mistral Medium 3.5: 52.1 (#93)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Non-English14171405
LMArena Chinese14951443
LMArena French14321448
LMArena German14261453
LMArena Korean14011387
LMArena Russian14231396
LMArena Spanish14331406
LMArena Japanese1439—

Instruction Following Too close to call

GLM-4.7: 74.6 (#90), Mistral Medium 3.5: 74.7 (#87)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Instruction Following14111414

Long Context Too close to call

GLM-4.7: 42.8 (#111), Mistral Medium 3.5: 43.2 (#101)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Longer Query14321414
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 61.1 (#89), Mistral Medium 3.5: 58.6 (#113)

BenchmarkGLM-4.7Mistral Medium 3.5
LMArena Text14361421
LMArena Creative Writing14011372
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 41.7 to 39.6 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: 43.6 versus 35.7 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.

Related comparisons

Go deeper