Noometry

Model comparison

GLM-4.7 vs Mistral Large

GLM-4.7 is the stronger model overall, scoring 42.0 to 31.9 on the Noometry Index.

Last verified . 27 shared benchmarks.

GLM-4.7 Z.ai (Zhipu)

42.0

Rank #124 Confirmed

Mistral Large Mistral AI

31.9

Rank #263 Confirmed

Summary

  • They share 27 benchmarks with published results for both. GLM-4.7 scores higher in 8 categories and Mistral Large in 1 category; 9 gaps are clear of the uncertainty.
  • The widest gap is in math, where GLM-4.7 leads 38.6 to 18.2.
  • The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 83.3% for GLM-4.7 and 8.5% for Mistral Large.
  • GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $2 / $6 for Mistral Large.
  • GLM-4.7 accepts more context: 205K tokens versus 131K.

Side by side

GLM-4.7Mistral Large
ProviderZ.ai (Zhipu)Mistral AI
Noometry Index42.031.9
Released2025-12-222024-02-26
WeightsOpenOpen
Context window205K131K
Max output131K16K
Input $ / M tokens$0.60$2
Output $ / M tokens$2.20$6
Results tracked3651

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Category by category

Coding GLM-4.7 leads

GLM-4.7: 44.0 (#79), Mistral Large: 34.3 (#240)

BenchmarkGLM-4.7Mistral Large
SciCode45.1%36.2%
LMArena Coding14541277
ALE-Bench399.48264.7
LMArena WebDev1435—
BigCodeBench Instruct—30%
LiveBench Coding—47.1%
BigCodeBench Complete—38.3%
HumanEval+—62.2%
MBPP+—59.5%

Agentic & Tool Use Mistral Large leads

GLM-4.7: 26.5 (#103), Mistral Large: 28.6 (#89)

BenchmarkGLM-4.7Mistral Large
Terminal-Bench33.4%—
Berkeley Function Calling Leaderboard—38.4%
Vending-Bench 22,377—

Reasoning GLM-4.7 leads

GLM-4.7: 24.3 (#164), Mistral Large: 15.8 (#310)

BenchmarkGLM-4.7Mistral Large
SimpleBench47.7%22.5%
CritPt1.7%0%
LMArena Hard Prompts14431257
Epoch Capabilities Index143.51128.52
Chess Puzzles6%—
LiveBench Reasoning—43.5%
DTBench—65.1%
LiveBench Data Analysis—50.1%
LMCA—16.7%
ForecastBench—57.1
LiveBench—48.4%

Math GLM-4.7 leads

GLM-4.7: 38.6 (#135), Mistral Large: 18.2 (#291)

BenchmarkGLM-4.7Mistral Large
OTIS Mock AIME 2024-202583.3%8.5%
LMArena Math14231262
FrontierMath (Feb 2025 set)2.4%0.3%
ProofBench6%—
Omni-MATH—28.1%
LiveBench Math—42.5%
MATH Level 5—50.3%
FrontierMath Tier 4 (v1)0%—

Knowledge GLM-4.7 leads

GLM-4.7: 47.0 (#80), Mistral Large: 30.1 (#230)

BenchmarkGLM-4.7Mistral Large
GPQA Diamond83.3%51.3%
Vectara Hallucination Rate11.7%4.5%
LMArena Expert14241232
SimpleQA Verified32.2%—
MMLU-Pro—59.9%
Confabulations—21.4%
GPQA (HELM)—43.5%
MMLU—80%

Multilingual GLM-4.7 leads

GLM-4.7: 52.8 (#79), Mistral Large: 40.0 (#219)

BenchmarkGLM-4.7Mistral Large
LMArena Non-English14171237
LMArena Chinese14951240
LMArena French14321325
LMArena German14241254
LMArena Japanese14391188
LMArena Korean13991202
LMArena Russian14231257
LMArena Spanish14341268

Instruction Following GLM-4.7 leads

GLM-4.7: 74.4 (#95), Mistral Large: 67.9 (#191)

BenchmarkGLM-4.7Mistral Large
LMArena Instruction Following14111249
LiveBench Instruction Following—67.9%
IFEval—87.7%

Long Context GLM-4.7 leads

GLM-4.7: 42.8 (#116), Mistral Large: 38.3 (#199)

BenchmarkGLM-4.7Mistral Large
LMArena Longer Query14321261
CL-bench15.9%—
CL-bench Life10.9%—

Writing & Preference GLM-4.7 leads

GLM-4.7: 60.9 (#93), Mistral Large: 40.7 (#242)

BenchmarkGLM-4.7Mistral Large
LMArena Text14351266
LMArena Creative Writing14011243
EQ-Bench Creative Writing1413985
LMArena Multi-Turn14461260
Short-Story Creative Writing—69%
WildBench—80.1%
LiveBench Language—39.4%

Frequently asked questions

Is GLM-4.7 better than Mistral Large?

GLM-4.7 is the stronger model overall, scoring 42.0 to 31.9 on the Noometry Index.

Which is cheaper, GLM-4.7 or Mistral Large?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Mistral Large lists at $2 and $6.

Is GLM-4.7 or Mistral Large better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 34.3 in the Noometry coding category.

Which has the bigger context window?

GLM-4.7 does, with 205K tokens against 131K.

How many benchmarks do GLM-4.7 and Mistral Large share?

27 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Mistral Large has 51.

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