GLM-5.2 vs Qwen3.8 2.4T A95B
GLM-5.2 
Qwen3.8 2.4T A95B Verdict
- Qwen3.8 2.4T A95B leads on quality: 65.2 vs 63.9.
- GLM-5.2 (max) is stronger in coding, human preference, instruction following, maths.
- Qwen3.8 2.4T A95B is stronger in agents & tools, composite, knowledge, long context, reasoning.
- GLM-5.2 (max) is 1.4× cheaper ($2.15 vs $3.00 per 1M blended).
- GLM-5.2 (max) streams 1.9× faster (71 vs 38 tokens per second).
| Metric | GLM-5.2 (max) | Qwen3.8 2.4T A95B |
|---|---|---|
| BenchLeader Index | 63.9 | 65.2 |
| Agents & tools score | 63.8 | 78.3 |
| Coding score | 63.8 | – |
| Composite score | 72.1 | 79.8 |
| Human preference score | 67.2 | – |
| Instruction following score | 71.6 | – |
| Knowledge score | 55.5 | 66.3 |
| Long context score | 65.6 | 66.6 |
| Maths score | 59.0 | – |
| Reasoning score | 72.9 | 80.5 |
| Blended price $/M | $2.15 | $3.00 |
| Output speed | 71 tok/s | 38 tok/s |
| Time to first answer | 31.6 s | 55.2 s |
| Context window | 1M | 984k |
| GPQA Diamond | 91.9% | – |
| FrontierMath Tiers 1–3 | 59.2% | – |
| FrontierMath Tier 4 | 29.3% | – |
| OTIS Mock AIME | 86.4% | – |
| SWE-bench Verified (Epoch) | 78.7% | – |
| SimpleQA Verified | 34.2% | – |
| SciCode | 50.5% | – |
| WeirdML | 70.1% | – |
| ProofBench | 35.0% | – |
| LMArena Text | 1472 | – |
| LMArena Hard Prompts | 1493 | – |
| LMArena Coding | 1510 | – |
| LMArena WebDev | 1592 | – |
| LMArena Agent | 4.4 | – |
| AA Intelligence Index | 34.0 | 40.0 |
| IFBench | 73.3% | – |
| AA-LCR | 78.3% | 80.3% |
| AA-Omniscience | 4.4 | 4.3 |
| Terminal-Bench Hard | 50.8% | – |
| GPQA Diamond (AA) | 89.5% | 93.5% |
| Humanity's Last Exam (AA) | 41.1% | 42.5% |
| SciCode (AA) | 51.2% | 54.0% |
| τ²-Bench Telecom (AA) | 99.1% | – |
| Terminal-Bench 2.1 (Vals) | 67.8% | – |
| SWE-bench (Vals) | 82.8% | – |
| CritPt | 20.9% | 20.0% |
| GDPval (AA) | 45.3% | 56.4% |
| τ²-Bench Banking (AA) | 34.6% | 49.1% |
| ITBench SRE (AA) | 42.7% | – |
| APEX-Agents (AA) | 33.7% | – |
| Code Migration | 37.9% | – |
| Harvey's Legal Agent Benchmark | 7.1% | – |
| Legal Research Bench | 31.3% | – |
| ProgramBench | 0.5% | – |
| SkillsBench | 45.1% | – |
| SREBench | 0.0% | – |
| Vibe Code Bench v1.1 | 64.0% | – |
| LMArena Maths | 1480 | – |
| LMArena Creative Writing | 1451 | – |
| LMArena Instruction Following | 1466 | – |
| LMArena Multi-turn | 1469 | – |
| LMArena Longer Queries | 1483 | – |
| Chess Puzzles | 21.0% | – |
| EBR-bench | 9.5% | – |
| PostTrainBench | 31.7% | – |
| DeepSWE | 43.8% | – |
| LMCA | 45.8% | – |
| DTBench | 93.6% | – |
| CursorBench | 55.0% | – |
| ALE-Bench | 1010.2 | – |
Data as of 2026-09-19. Best configuration of each model; every score links to its source on the model pages.
GLM-5.2 vs Qwen3.8 2.4T A95B: questions
- Is GLM-5.2 better than Qwen3.8 2.4T A95B?
- Qwen3.8 2.4T A95B leads on quality: 65.2 vs 63.9. The BenchLeader Index combines every independent quality benchmark; Qwen3.8 2.4T A95B is ahead overall as of 2026-09-19, but check the category scores for your use.
- Is GLM-5.2 better than Qwen3.8 2.4T A95B for agentic tasks?
- Qwen3.8 2.4T A95B scores higher in agentic tasks (78 vs 64 on the category index, where 50 is average).
- Which is cheaper, GLM-5.2 or Qwen3.8 2.4T A95B?
- GLM-5.2 is cheaper: $2.15 against $3.00 per million tokens, blended at three input tokens per output token.
- Which is faster, GLM-5.2 or Qwen3.8 2.4T A95B?
- GLM-5.2 streams faster: 71 against 38 output tokens per second.
- Which has the larger context window?
- GLM-5.2 accepts more context: 1M against 984k tokens.