GLM 5.3 Flash vs Muse Wonder
Full profiles: GLM 5.3 Flash (Zhipu AI) and Muse Wonder (Meta): every benchmark, price and rank.
Updated · Data from 7 sources
As of 24 Oct 2026, GLM 5.3 Flash and Muse Wonder (max) are neck and neck on quality (62.6 vs 67.5 on the BenchLeader Index, inside the ±5.9 margin of error), and GLM 5.3 Flash costs 34× less, which makes it the better buy for most workloads. Pick GLM 5.3 Flash for agents & tools (59 vs 56); pick Muse Wonder for reasoning (81 vs 66).
GLM 5.3 Flash benchmarks 
Muse Wonder benchmarks Which to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Coding | Muse Wonder | 66 vs 63 category score; Arena WebDev 1651 vs 1608 | Medium |
| Agents & tool use | GLM 5.3 Flash | 59 vs 56 category score; Arena Agent -1.6 vs 3.7 | Medium |
| Maths | Either | 69 vs 68 category score; Arena Maths 1504 vs 1496 | Either |
| Reasoning | Muse Wonder | 81 vs 66 category score; CritPt 28.3% vs 15.4% | High |
| Knowledge | Muse Wonder | 73 vs 65 category score; AA-Omniscience 25.5 vs 7.5 | High |
| Long documents | Either | 65 vs 65 category score; AA-LCR 80.0% vs 80.7% | Either |
| Chat quality (human preference) | Muse Wonder | 71 vs 67 on Arena votes | Medium |
| Lowest cost | GLM 5.3 Flash | $0.238 vs $8.00 per 1M blended; agentic coding session $0.011 vs $0.320 | – |
| Fastest first answer | Either | 32.4 s (GLM 5.3 Flash) vs 40.3 s (Muse Wonder (max)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- GLM 5.3 Flash and Muse Wonder (max) are neck and neck on quality (62.6 vs 67.5, within the ±5.9 margin).
- GLM 5.3 Flash is stronger in agents & tools, maths, multimodal.
- Muse Wonder (max) is stronger in coding, composite, human preference, knowledge, long context, reasoning.
- GLM 5.3 Flash is 34× cheaper ($0.238 vs $8.00 per 1M blended).
- Muse Wonder (max) streams 2.1× faster (145 vs 69 tokens per second).
At a glance
| Spec | GLM 5.3 Flash | Muse Wonder |
|---|---|---|
| Developer | Zhipu AI | Meta |
| Released | 20 Aug 2026 | 12 Oct 2026 |
| Context window (tokens) | 1,000,000 | 1,048,576 |
| Compared at | GLM 5.3 Flash | Muse Wonder (max) |
| Open weights | Yes | No |
| Price in / out / cached input per 1M | $0.150 / $0.500 / $0.030 | $4.00 / $20.00 / $0.200 |
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | GLM 5.3 Flash | Muse Wonder (max) | Leader |
|---|---|---|---|
| Reasoning | 66.4 | 81.3 | Muse Wonder |
| Coding | 62.9 | 66.2 | Muse Wonder |
| Agents & tools | 59.4 | 55.9 | GLM 5.3 Flash |
| Maths | 68.7 | 67.8 | level |
| Knowledge | 64.9 | 73.0 | Muse Wonder |
| Human preference | 66.7 | 70.7 | Muse Wonder |
| Multimodal | 63.8 | – | not comparable |
| Long context | 65.0 | 65.4 | level |
| Composite | 64.9 | 88.1 | Muse Wonder |
Where sources disagree
Across the 33 benchmarks both have, GLM 5.3 Flash leads 1, Muse Wonder leads 32. Every overall index that rates both puts Muse Wonder ahead.
| Overall index | GLM 5.3 Flash | Muse Wonder (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 62.6 | 67.5 | neck and neck |
| AA Intelligence Index v4.3.2 | 41.8 | 52.4 | Muse Wonder |
| Vals Index | 50.9† | 64.9 | Muse Wonder |
| Arena Text | 1476 | 1509 | Muse Wonder |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | GLM 5.3 Flash | Muse Wonder (max) |
|---|---|---|
| Blended price per 1M tokens | $0.238 | $8.00 |
| Input / output per 1M | $0.150 / $0.500 | $4.00 / $20.00 |
| Cached input per 1M | $0.030 | $0.200 |
| Price per task: chat reply | $0.0002 | $0.0076 |
| Price per task: summarize a 30-page report | $0.0021 | $0.060 |
| Price per task: code edit | $0.0017 | $0.054 |
| Price per task: agentic coding session | $0.011 | $0.320 |
| Price per task: structured extraction | $0.0004 | $0.012 |
| Cost to run a full benchmark suite | $0.284 | $4.54 |
| Output speed | 69 tok/s | 145 tok/s |
| Time to first answer | 32.4 s | 40.3 s |
| Time to a complete answer | 39.7 s | 43.8 s |
Per token is not per task: on Artificial Analysis' full suite GLM 5.3 Flash cost $0.284 and Muse Wonder (max) $4.54, because GLM 5.3 Flash used about 2.1× as many tokens for the same work, which a per-token price hides.
Each model is compared at its best-ranked reasoning-effort setting. GLM 5.3 Flash scores 62.6 and takes 32 s to its first answer token; GLM 5.3 Flash (max) scores 54.2 in 32 s. Muse Wonder (max) scores 67.5 and takes 40 s to its first answer token; Muse Wonder scores 63.7 in 3 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
120 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | GLM 5.3 Flash | Muse Wonder (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 62.6 | 67.5 |
| Agents & tools score | BenchLeader | 59.4 | 55.9 |
| Coding score | BenchLeader | 62.9 | 66.2 |
| Composite score | BenchLeader | 64.9 | 88.1 |
| Human preference score | BenchLeader | 66.7 | 70.7 |
| Knowledge score | BenchLeader | 64.9 | 73.0 |
| Long context score | BenchLeader | 65.0 | 65.4 |
| Maths score | BenchLeader | 68.7 | 67.8 |
| Multimodal score | BenchLeader | 63.8 | – |
| Reasoning score | BenchLeader | 66.4 | 81.3 |
| Blended price $/M | BenchLeader | $0.238 | $8.00 |
| Output speed | BenchLeader | 69 tok/s | 145 tok/s |
| Time to first answer | BenchLeader | 32.4 s | 40.3 s |
| Context window | BenchLeader | 1,000,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 90.2%† | – |
| Arena Hard Prompts | Arena (LMArena) | 1501 | 1522 |
| LiveBench 2.0 Reasoning | LiveBench | 77.6% | 90.6%† |
| LiveBench 1.0 Reasoning | LiveBench | 77.6% | 90.6% |
| GPQA Diamond (AA) | Artificial Analysis | 91.2% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 39.9% | 50.1% |
| GPQA Diamond (Vals) | Vals AI | 86.4%† | – |
| ARC-AGI-1 | ARC Prize | 91.0%† | – |
| ARC-AGI-2 | ARC Prize | 65.8%† | – |
| CritPt | Artificial Analysis | 15.4% | 28.3% |
| MysteryMechanism | Vals AI | – | 27.5% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 21.0%† | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 8.0%† | 51.0% |
| LMCA | Epoch AI Benchmarking Hub | – | 56.8%† |
| DTBench | Epoch AI Benchmarking Hub | – | 95.2%† |
| BTF-3 | Epoch AI Benchmarking Hub | 14.9% | – |
| Coding | |||
| SciCode | SciCode | 51.6% | 60.3% |
| FrontierCode | Cognition | 31.8%† | – |
| Arena Coding | Arena (LMArena) | 1525 | 1545 |
| Arena WebDev | Arena (LMArena) | 1608 | 1651 |
| LiveBench 2.0 Coding | LiveBench | 80.6% | 86.2%† |
| LiveBench 1.0 Coding | LiveBench | 79.0% | 80.7% |
| LiveCodeBench | Vals AI | 80.5%† | – |
| IOI | Vals AI | 52.5%† | 66.9% |
| SWE-bench (Vals) | Vals AI | 92.0%† | – |
Show all 120 benchmarks
| Metric | Publisher | GLM 5.3 Flash | Muse Wonder (max) |
|---|---|---|---|
| Coding | |||
| Code Migration | Vals AI | 20.5%† | 62.5% |
| Code Migration v1.1 | Vals AI | 51.6%† | 72.4% |
| ProgramBench | Vals AI | 0.0%† | – |
| SWE-bench Multimodal | Vals AI | – | 45.6% |
| Vibe Code Bench 1-100 | Vals AI | 16.0%† | 26.6% |
| Vibe Code Bench v1.1 | Vals AI | 30.8%† | 83.1% |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 52.5%† | – |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 63.4%† | – |
| CursorBench | Cursor | 36.8%† | 50.4% |
| ALE-Bench | Epoch AI Benchmarking Hub | 303.6† | – |
| FrontierSWE | Epoch AI Benchmarking Hub | 18.1%† | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 32.8% | 52.0% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 84.3% | – |
| FrontierCode 1.1 (AA) | Artificial Analysis | 41.0% | 46.5% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 35.8%† | – |
| APEX-Agents | Mercor | 52.8% | – |
| Arena Agent | Arena (LMArena) | -1.6 | 3.7 |
| LiveBench Long Agentic | LiveBench | 28.4% | 53.2%† |
| LiveBench Browser | LiveBench | 84.0% | 72.0%† |
| LiveBench Agentic Coding | LiveBench | 56.8% | 62.7% |
| Terminal-Bench 2.1 (Vals) | Vals AI | 62.9%† | – |
| HiL-Bench | Scale AI SEAL | – | 79.7%† |
| GDPval-AA v2.1 | Artificial Analysis | 57.1% | 63.5% |
| τ³-Banking (AA) | Artificial Analysis | 47.2% | – |
| ITBench SRE (AA) | Artificial Analysis | 51.2% | – |
| Analyst Agent (AA) | Artificial Analysis | 25.0% | – |
| CUA-bench | Vals AI | – | 7.2% |
| CyberBench | Vals AI | 67.9%† | 80.4% |
| Finance Agent v2 | Vals AI | 57.9%† | 56.6% |
| Finance Agent v2.1 | Vals AI | 60.6%† | 65.5% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 10.4%† | 23.8% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 6.7%† | 17.1% |
| Legal Research Bench | Vals AI | 45.2%† | 50.5% |
| SkillsBench | Vals AI | 40.2%† | – |
| SREBench | Vals AI | 0.8%† | – |
| Tax Agent Bench | Vals AI | 31.6%† | 36.3% |
| Terminal-Bench 4.0 (Vals) | Vals AI | 37.4%† | 49.5% |
| Terminal-Bench Science | Vals AI | 2.9%† | 22.9% |
| Vending-Bench 2 | Andon Labs | – | 9432.2† |
| AutomationBench | Artificial Analysis | 60.4% | 68.1% |
| GDP.pdf (AA) | Artificial Analysis | 15.4% | 30.6% |
| Harvey LAB-AA v1.1 | Harvey | 0.8% | 10.0% |
| EnterpriseOps-Gym | Artificial Analysis | 33.2% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1453 | 1659 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 4.8% | 25.7% |
| CWE-Bench (AA) | Artificial Analysis | 55.8% | – |
| DeepSec-Bench (AA) | Artificial Analysis | 19.9% | – |
| CyberGym end-to-end (AA) | Artificial Analysis | 74.0% | – |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 55.8%† | 82.1% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 17.1%† | 70.7% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 93.9%† | 99.4% |
| ProofBench | Vals AI | 21.0%† | 84.0%† |
| LiveBench Mathematics | LiveBench | 81.2% | 96.5% |
| Arena Maths | Arena (LMArena) | 1504 | 1496 |
| Knowledge | |||
| LiveBench 2.0 Data Analysis | LiveBench | 76.4% | 81.6%† |
| LiveBench Research | LiveBench | 70.1% | 88.0%† |
| LiveBench 1.0 Data Analysis | LiveBench | 76.4% | 81.6% |
| AA-Omniscience | Artificial Analysis | 7.5 | 25.5 |
| MMLU-Pro | Vals AI | 86.1%† | – |
| LegalBench | Vals AI | 83.9%† | – |
| TaxEval | Vals AI | 75.6%† | – |
| PRBench Finance | Scale AI SEAL | – | 58.7%† |
| PRBench Legal | Scale AI SEAL | – | 58.4%† |
| BioMysteryBench | Vals AI | – | 67.0% |
| Excel Modeling Benchmark | Vals AI | 55.9%† | 67.1% |
| Excel Modeling Benchmark v1.1 | Vals AI | 66.3%† | 72.5% |
| MedScribe | Vals AI | 88.9%† | – |
| Public Benefits Bench v1.1 | Vals AI | – | 70.2% |
| EBR-bench | Epoch AI Benchmarking Hub | – | 31.4% |
| GDP.pdf | Epoch AI Benchmarking Hub | 14.0%† | 30.8% |
| AA-Omniscience: accuracy | Artificial Analysis | 27.5% | 41.1% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 72.4% | 73.5% |
| Instruction following | |||
| LiveBench Language | LiveBench | 77.3% | 82.9% |
| LiveBench Instruction Following | LiveBench | 52.8% | 73.0% |
| Arena Instruction Following | Arena (LMArena) | 1473 | 1498 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1476 | 1509 |
| Arena Creative Writing | Arena (LMArena) | 1434 | 1492 |
| Arena Multi-turn | Arena (LMArena) | 1476 | 1519 |
| Arena Longer Queries | Arena (LMArena) | 1481 | 1502 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1294 | – |
| LiveBench Design | LiveBench | 77.2% | 75.1%† |
| MMMU-Pro (Vals) | Vals AI | 86.0%† | – |
| AA-3D | Artificial Analysis | 935 | – |
| Long context | |||
| AA-LCR | Artificial Analysis | 80.0% | 80.7% |
| MLCR | Artificial Analysis | 11.7% | 22.2% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 153.1 | 161.8† |
| LiveBench 2.0 | LiveBench | 70.6% | 78.1%† |
| LiveBench 1.0 | LiveBench | 71.6% | 81.2% |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 41.8 | 52.4 |
| Vals Index | Vals AI | 50.9† | 64.9 |
| Vals Finance Index | Vals AI | 55.8%† | 61.2% |
| Vals Science Index | Vals AI | – | 39.1% |
| Vals Router Index | Vals AI | 50.9% | 64.9%† |
| AA Cyber Index | Artificial Analysis | 49.9 | – |
| Metadata | |||
| AA Openness Index | Artificial Analysis | 44.4 | – |
Data as of 2026-10-24. Best configuration of each model; every score links to its source on the model pages.
What changed
- GLM 5.3 Flash: GLM 5.3 Flash cached input price moved from $0.034/M to $0.030/M (13% down).
- GLM 5.3 Flash: 1 new result (Vals Router Index).
- Muse Wonder (max): 8 new results (MLCR, Code Migration v1.1, Excel Modeling Benchmark v1.1…).
- Muse Wonder (max): 2 new results (FrontierCode 1.1 (AA), Terminal-Bench-Science 0.1 (AA)).
- GLM 5.3 Flash: 1 score revision.
- Muse Wonder (max): 1 new result (Arena Maths); 2 score revisions.
- GLM 5.3 Flash: 1 score revision; GLM 5.3 Flash cached input price moved from $0.03/M to $0.03/M (15% up).
- Muse Wonder (max): 3 score revisions.
- GLM 5.3 Flash: BenchLeader Index 62.4 → 62.9.
- Muse Wonder (max): BenchLeader Index 67.1 → 67.6.
Related comparisons
- GLM 5.3 Flash vs Claude Opus 5.5
- GLM 5.3 Flash vs Gemini 4 Argon
- GLM 5.3 Flash vs Muse Wonder Full
- Muse Wonder vs Claude Opus 5.5
- Muse Wonder vs Gemini 4 Argon
- Muse Wonder vs Muse Wonder Full
- Muse Wonder vs Claude Fable 5.1
- GLM 5.3 vs Muse Wonder
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GLM 5.3 Flash vs Muse Wonder: questions
- Is GLM 5.3 Flash better than Muse Wonder?
- GLM 5.3 Flash and Muse Wonder (max) are neck and neck on quality (62.6 vs 67.5, within the ±5.9 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-24, so check the category scores for your use.
- Which is cheaper, GLM 5.3 Flash or Muse Wonder, and will that change?
- GLM 5.3 Flash is cheaper today: $0.238 against $8.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is GLM 5.3 Flash better than Muse Wonder for coding?
- Muse Wonder scores higher in coding (66 vs 63 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1608 for GLM 5.3 Flash against 1651 for Muse Wonder.
- Is GLM 5.3 Flash better than Muse Wonder for agents and tool use?
- GLM 5.3 Flash scores higher in agentic tasks (59 vs 56 on the category index, where 50 is average). On Arena Agent, the top shared agents & tools benchmark, it is -1.6 for GLM 5.3 Flash against 3.7 for Muse Wonder.
- Which is better for long documents?
- They are level on long-context benchmarks (65 vs 65). Both take about 1M tokens: GLM 5.3 Flash 1,000,000, Muse Wonder 1,048,576.
- Which has lower latency?
- GLM 5.3 Flash answers first: 32.4 s against 40.3 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Which is faster, GLM 5.3 Flash or Muse Wonder?
- Muse Wonder streams faster: 145 against 69 output tokens per second.
- Do independent benchmarks agree on GLM 5.3 Flash vs Muse Wonder?
- Across the 33 benchmarks both have, GLM 5.3 Flash leads 1, Muse Wonder leads 32. Every overall index that rates both puts Muse Wonder ahead.
- When was Muse Wonder released?
- Muse Wonder was released on 12 Oct 2026.