Model comparison

GLM-4.6 vs Qwen3 Coder Next

GLM-4.6 is the stronger model overall, scoring 40.9 to 33.8 on the Noometry Index. Qwen3 Coder Next costs 3.4× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

Last verified . 2 shared benchmarks.

GLM-4.6 Z.ai (Zhipu)

40.9

Rank #132 Confirmed

Qwen3 Coder Next Alibaba (Qwen)

33.8

Rank #229 Reported

Summary

  • They share 2 benchmarks with published results for both. GLM-4.6 scores higher in 2 categories and Qwen3 Coder Next in 0 categories; 2 gaps are clear of the uncertainty.
  • The widest gap is in coding, where GLM-4.6 leads 39.9 to 35.8.
  • The biggest single-benchmark swing is SciCode: 38.4% for GLM-4.6 and 32.3% for Qwen3 Coder Next.
  • Qwen3 Coder Next is cheaper at $0.12 / $0.80 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
  • Qwen3 Coder Next accepts more context: 262K tokens versus 205K.

Side by side

GLM-4.6 and Qwen3 Coder Next specifications
GLM-4.6Qwen3 Coder Next
ProviderZ.ai (Zhipu)Alibaba (Qwen)
Noometry Index40.933.8
Released2025-09-302026-02-02
WeightsOpenOpen
Context window205K262K
Max output131K66K
Input $ / M tokens$0.60$0.12
Output $ / M tokens$2.20$0.80
Results tracked293

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Category by category

Coding GLM-4.6 leads

GLM-4.6: 39.9 (#137), Qwen3 Coder Next: 35.8 (#206)

Coding benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
SciCode38.4%32.3%
SWE-bench Verified (bash only)55.4%—
LMArena WebDev1339—
WeirdML—34.4%
LMArena Coding1449—
ALE-Bench340.82—

Agentic & Tool Use Not comparable

GLM-4.6: 32.1 (#60), Qwen3 Coder Next: —

Agentic & Tool Use benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
Terminal-Bench24.5%—
Berkeley Function Calling Leaderboard72.4%—

Reasoning GLM-4.6 leads

GLM-4.6: 23.1 (#168), Qwen3 Coder Next: 21.7 (#191)

Reasoning benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
CritPt1.1%0%
Kagi LLM Benchmark47.4%—
LMArena Hard Prompts1440—

Math Not comparable

GLM-4.6: 36.4 (#115), Qwen3 Coder Next: —

Math benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
LMArena Math1431—
FrontierMath (Feb 2025 set)3.8%—
FrontierMath Tier 4 (v1)2.1%—

Knowledge Not comparable

GLM-4.6: 39.6 (#118), Qwen3 Coder Next: —

Knowledge benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
Vectara Hallucination Rate9.5%—
LMArena Expert1432—

Multilingual Not comparable

GLM-4.6: 53.6 (#62), Qwen3 Coder Next: —

Multilingual benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
LMArena Non-English1426—
LMArena Chinese1500—
LMArena French1459—
LMArena German1447—
LMArena Japanese1394—
LMArena Korean1401—
LMArena Russian1418—
LMArena Spanish1436—

Instruction Following Not comparable

GLM-4.6: 74.5 (#93), Qwen3 Coder Next: —

Instruction Following benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
LMArena Instruction Following1410—

Long Context Not comparable

GLM-4.6: 43.4 (#91), Qwen3 Coder Next: —

Long Context benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
LMArena Longer Query1423—

Writing & Preference Not comparable

GLM-4.6: 61.3 (#86), Qwen3 Coder Next: —

Writing & Preference benchmarks
BenchmarkGLM-4.6Qwen3 Coder Next
LMArena Text1440—
LMArena Creative Writing1411—
EQ-Bench Creative Writing1411—
LMArena Multi-Turn1427—

Frequently asked questions

Is GLM-4.6 better than Qwen3 Coder Next?

GLM-4.6 is the stronger model overall, scoring 40.9 to 33.8 on the Noometry Index. Qwen3 Coder Next costs 3.4× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

Which is cheaper, GLM-4.6 or Qwen3 Coder Next?

Qwen3 Coder Next is cheaper. It lists at $0.12 per million input tokens and $0.80 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

Is GLM-4.6 or Qwen3 Coder Next better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 35.8 in the Noometry coding category.

Which has the bigger context window?

Qwen3 Coder Next does, with 262K tokens against 205K.

How many benchmarks do GLM-4.6 and Qwen3 Coder Next share?

2 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Qwen3 Coder Next has 3.

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