GLM-5.2 vs Qwen3.8-Flash-Next
GLM-5.2 
Qwen3.8-Flash-Next Verdict
- GLM-5.2 (max) leads on quality: 63.9 vs 61.6.
- GLM-5.2 (max) is stronger in composite, human preference, instruction following, maths, reasoning.
- Qwen3.8-Flash-Next is stronger in agents & tools, coding, knowledge, long context, multimodal.
- Qwen3.8-Flash-Next is 9.3× cheaper ($0.230 vs $2.15 per 1M blended).
| Metric | GLM-5.2 (max) | Qwen3.8-Flash-Next |
|---|---|---|
| BenchLeader Index | 63.9 | 61.6 |
| Agents & tools score | 63.8 | 65.8 |
| Coding score | 63.8 | 71.2 |
| Composite score | 72.1 | 67.4 |
| Human preference score | 67.2 | – |
| Instruction following score | 71.6 | – |
| Knowledge score | 55.5 | 59.6 |
| Long context score | 65.6 | 66.3 |
| Maths score | 59.0 | – |
| Reasoning score | 72.9 | 63.4 |
| Multimodal score | – | 64.3 |
| Blended price $/M | $2.15 | $0.230 |
| Output speed | 71 tok/s | 55 tok/s |
| Time to first answer | 31.6 s | 39.0 s |
| Context window | 1M | 256k |
| 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 | 1635 |
| LMArena Agent | 4.4 | -0.1 |
| LiveBench | – | 76.2% |
| LiveBench Reasoning | – | 87.4% |
| LiveBench Coding | – | 72.5% |
| LiveBench Agentic Coding | – | 61.6% |
| LiveBench Mathematics | – | 85.8% |
| LiveBench Data Analysis | – | 74.2% |
| LiveBench Language | – | 74.6% |
| LiveBench Instruction Following | – | 77.1% |
| AA Intelligence Index | 34.0 | 39.9 |
| IFBench | 73.3% | – |
| AA-LCR | 78.3% | 79.7% |
| MMMU-Pro | – | 79.8% |
| AA-Omniscience | 4.4 | -9.7 |
| Terminal-Bench Hard | 50.8% | – |
| GPQA Diamond (AA) | 89.5% | 92.3% |
| Humanity's Last Exam (AA) | 41.1% | 38.0% |
| SciCode (AA) | 51.2% | 50.6% |
| τ²-Bench Telecom (AA) | 99.1% | – |
| Terminal-Bench 2.1 (Vals) | 67.8% | – |
| SWE-bench (Vals) | 82.8% | – |
| CritPt | 20.9% | 11.1% |
| GDPval (AA) | 45.3% | 57.4% |
| τ²-Bench Banking (AA) | 34.6% | 45.4% |
| 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-Flash-Next: questions
- Is GLM-5.2 better than Qwen3.8-Flash-Next?
- GLM-5.2 (max) leads on quality: 63.9 vs 61.6. The BenchLeader Index combines every independent quality benchmark; GLM-5.2 (max) is ahead overall as of 2026-09-19, but check the category scores for your use.
- Is GLM-5.2 better than Qwen3.8-Flash-Next for coding?
- Qwen3.8-Flash-Next scores higher in coding (71 vs 64 on the category index, where 50 is average).
- Is GLM-5.2 better than Qwen3.8-Flash-Next for agentic tasks?
- Qwen3.8-Flash-Next scores higher in agentic tasks (66 vs 64 on the category index, where 50 is average).
- Which is cheaper, GLM-5.2 or Qwen3.8-Flash-Next?
- Qwen3.8-Flash-Next is cheaper: $0.230 against $2.15 per million tokens, blended at three input tokens per output token.
- Which is faster, GLM-5.2 or Qwen3.8-Flash-Next?
- GLM-5.2 streams faster: 71 against 55 output tokens per second.
- Which has the larger context window?
- GLM-5.2 accepts more context: 1M against 256k tokens.