Model comparison

DeepSeek-R1-Distill-Llama-70B vs GLM-5

GLM-5 is the stronger model overall, scoring 46.1 to 37.8 on the Noometry Index.

Last verified October 10, 2026. 3 shared benchmarks.

DeepSeek-R1-Distill-Llama-70B

DeepSeek

37.8

Rank #195 Confirmed

GLM-5 Z.ai (Zhipu)

46.1

Rank #66 Confirmed

Summary

They share 3 benchmarks with published results for both. DeepSeek-R1-Distill-Llama-70B scores higher in 0 categories and GLM-5 in 6 categories; 6 gaps are clear of the uncertainty.
The widest gap is in knowledge, where GLM-5 leads 52.3 to 30.7.
The biggest single-benchmark swing is GPQA Diamond: 55.7% for DeepSeek-R1-Distill-Llama-70B and 87.8% for GLM-5.

Side by side

DeepSeek-R1-Distill-Llama-70B and GLM-5 specifications
	DeepSeek-R1-Distill-Llama-70B	GLM-5
Provider	DeepSeek	Z.ai (Zhipu)
Noometry Index	37.8	46.1
Released	2025-01-20	2026-02-11
Weights	Open	Open
Context window	—	205K
Max output	—	131K
Input $ / M tokens	—	$1
Output $ / M tokens	—	$3.20
Results tracked	13	45

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Category by category

Coding GLM-5 leads

DeepSeek-R1-Distill-Llama-70B: 36.8 (#202), GLM-5: 49.0 (#52)

Coding benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
SWE-bench Verified	—	72.1%
SWE-bench Verified (bash only)	—	72.8%
LMArena WebDev	—	1434
SWE-bench Multilingual	—	69.7%
WeirdML	—	48.2%
BigCodeBench Instruct	35.3%	—
LiveBench Coding	51.6%	—
LMArena Coding	—	1461
BigCodeBench Complete	49.9%	—
ALE-Bench	—	765.62

Agentic & Tool Use Not comparable

DeepSeek-R1-Distill-Llama-70B: —, GLM-5: 31.1 (#71)

Agentic & Tool Use benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
Terminal-Bench	—	52.4%
τ²-bench Airline	—	82.5%
τ²-bench Banking	—	9.8%
τ²-bench Retail	—	73.7%
τ²-bench Telecom	—	86.8%
Vending-Bench 2	—	4,432

Reasoning GLM-5 leads

DeepSeek-R1-Distill-Llama-70B: 24.9 (#156), GLM-5: 27.6 (#116)

Reasoning benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
Kagi LLM Benchmark	52.3%	75%
ARC-AGI-2	—	4.9%
SimpleBench	—	53.2%
NYT Connections (extended)	—	74.8%
ARC-AGI-1	—	44.7%
Chess Puzzles	—	10%
LiveBench Reasoning	67.6%	—
LMArena Hard Prompts	—	1452
LiveBench Data Analysis	55.9%	—
Epoch Capabilities Index	—	145.83
ForecastBench	—	61
LiveBench	54.5%	—

Math GLM-5 leads

DeepSeek-R1-Distill-Llama-70B: 36.0 (#176), GLM-5: 46.4 (#71)

Math benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
OTIS Mock AIME 2024-2025	51.4%	80%
MathArena Final-Answer Competitions	—	65.7%
LiveBench Math	58.1%	—
LMArena Math	—	1440
MATH Level 5	89.9%	—
FrontierMath (Feb 2025 set)	—	16.4%
FrontierMath Tier 4 (v1)	—	2.1%

Knowledge GLM-5 leads

DeepSeek-R1-Distill-Llama-70B: 30.7 (#225), GLM-5: 52.3 (#64)

Knowledge benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
GPQA Diamond	55.7%	87.8%
Vectara Hallucination Rate	—	10.1%
LMArena Expert	—	1454

Multilingual Not comparable

DeepSeek-R1-Distill-Llama-70B: —, GLM-5: 53.7 (#58)

Multilingual benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
LMArena Non-English	—	1430
LMArena Chinese	—	1511
LMArena French	—	1455
LMArena German	—	1445
LMArena Japanese	—	1416
LMArena Korean	—	1423
LMArena Russian	—	1436
LMArena Spanish	—	1454

Instruction Following GLM-5 leads

DeepSeek-R1-Distill-Llama-70B: 68.2 (#190), GLM-5: 75.2 (#67)

Instruction Following benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
LiveBench Instruction Following	69.9%	—
LMArena Instruction Following	—	1428

Long Context Not comparable

DeepSeek-R1-Distill-Llama-70B: —, GLM-5: 44.7 (#60)

Long Context benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
CL-bench	—	18.7%
LMArena Longer Query	—	1446

Writing & Preference GLM-5 leads

DeepSeek-R1-Distill-Llama-70B: 49.0 (#194), GLM-5: 66.0 (#38)

Writing & Preference benchmarks
Benchmark	DeepSeek-R1-Distill-Llama-70B	GLM-5
LMArena Text	—	1446
LMArena Creative Writing	—	1439
EQ-Bench Creative Writing	—	1601
LMArena Multi-Turn	—	1456
LiveBench Language	23.8%	—

Frequently asked questions

Is DeepSeek-R1-Distill-Llama-70B better than GLM-5?