Qwen3-Coder-NextvsGLM-5.2
Qwen3-Coder-Next | GLM-5.2 | |
|---|---|---|
| Specifications | ||
Parameters | 80B | 744B |
Context window | 256k | 1M |
| Benchmarks | ||
Nonsense detection BullshitBench v2Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | — | 31% |
Agentic coding SWE-Bench ProCan the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. | 44.3% | 62.1%Best |
Coding SWE-Bench VerifiedReal coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | 70.6% | — |
Multilingual coding SWE-Bench MultilingualLike SWE-Bench, but the coding problems span many programming languages, not just one. Tests how broadly the AI can code. Higher is better. | 62.8% | — |
Agentic coding CursorBench v3.2Cursor's own test of harder, real-world coding tasks inside a code editor, on the refreshed v3.2 task set. Scores aren't comparable with v3.1. Higher is better. | — | 55% |
Agentic coding CursorBench v3.1Cursor's own test of harder, real-world coding tasks inside a code editor. Higher is better. | — | 54.6% |
Agentic coding DeepSWE 1.1Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | — | 44% |
Next.js coding Next.js EvalsVercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | — | 88% |
Agentic computer work Frontier-Bench v0.1A hard, ever-evolving set of real computer tasks — coding, system administration, data work, and more — that an AI agent has to complete on its own. Run by the Harbor / Laude Institute team as the successor to Terminal-Bench (v0.1 is the first release of the task set). The score is the share of tasks solved. Higher is better. | — | 5.1% |
Agentic terminal coding Terminal-Bench 2.1Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | — | 81% |
Agentic terminal coding Terminal-Bench 2.0Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? (Version 2.0 of the test.) Higher is better. | 36.2% | — |
Multidisciplinary reasoning Humanity's Last Exam · no toolsHumanity's Last Exam — extremely hard expert questions across many subjects, written so you can't just look up the answer. “No tools” means the AI answers on its own. Higher is better. | — | 40.5% |
Multidisciplinary reasoning Humanity's Last Exam · with toolsHumanity's Last Exam — extremely hard expert questions across many subjects. “With tools” means the AI is allowed to search the web or run code while answering. Higher is better. | — | 54.7% |
Science GPQA DiamondGraduate-level science questions in biology, physics, and chemistry — hard enough that subject-matter PhDs score around 65%. Higher is better. | — | 91.2% |
Knowledge work GDPval-AA v2economically valuable knowledge work (v2, re-based Elo) | — | 1514 |
Community preference (code) Arena Elo (Code)Like the text arena, but people vote on which AI writes better code. The votes become a chess-style Elo rating on arena.ai. Higher is better. | — | 1587 |
| Overview | ||
| Company | Qwen | Z.ai |
| Release date | Feb 3 2026 | Jun 16 2026 |
| Access | Open Weight | Open Weight |
Which is better: Qwen3-Coder-Next or GLM-5.2?
GLM-5.2 leads Qwen3-Coder-Next on 1 of the 1 benchmark they both report (SWE-Bench Pro). Qwen3-Coder-Next shipped 133 days before GLM-5.2, so benchmark comparisons should account for the intervening progress.
Qwen3-Coder-Next has 80B parameters, while GLM-5.2 has 744B. Context windows are 256k (Qwen3-Coder-Next) vs 1M (GLM-5.2).
On SWE-Bench Pro, GLM-5.2 leads at 62.1% vs Qwen3-Coder-Next at 44.3%.
Frequently asked questions
Qwen3-Coder-Next was released by Qwen on Feb 3 2026.
GLM-5.2 was released by Z.ai on Jun 16 2026.
GLM-5.2 leads on SWE-Bench Pro — Qwen3-Coder-Next 44.3% vs GLM-5.2 62.1%.
Qwen3-Coder-Next has a 256k context window; GLM-5.2 has 1M.
Other comparisons
Qwen3-Coder-NextvsClaude Opus 5GLM-5.2vsClaude Opus 5Qwen3-Coder-NextvsGPT-5.6 SolGLM-5.2vsGPT-5.6 SolQwen3-Coder-NextvsGemini 3.6 FlashGLM-5.2vsGemini 3.6 FlashQwen3-Coder-NextvsMuse Spark 1.1GLM-5.2vsMuse Spark 1.1Qwen3-Coder-NextvsGrok 4.5GLM-5.2vsGrok 4.5Qwen3-Coder-NextvsDeepSeek-V4-Flash-0731GLM-5.2vsDeepSeek-V4-Flash-0731