Model comparison
GLM 5.3 vs Qwen3-Max
Z.ai against Qwen, compared on context, price, and verified benchmark results.
Catalog record checked September 3, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
Z.ai
GLM 5.3
Frontier · Open weights
Qwen
Qwen3-Max
Frontier
| Specification | GLM 5.3 | Qwen3-Max |
|---|---|---|
| Provider | Z.ai | Qwen |
| Tier | Frontier | Frontier |
| Context window | Winner: 1M | 262K |
| Max output | Winner: 128K | 66K |
| Input / 1M tokens | $1.40 | Winner: $1.20 |
| Output / 1M tokens | Winner: $4.40 | $6 |
| Weights | Open | Closed |
| Parameters | 753B total (MoE; active count unpublished) | 1T (proprietary) |
| Reasoning levels | low, high, max | low, high, max |
| Modalities | text | text, image, video |
| License | glm-5.3 (custom) | Not disclosedUnverified |
| API model id | glm-5.3 | qwen3-max |
| Released | August 14, 2026 | September 23, 2025 |
| Artificial Analysis Intelligence Index [max] (2026-08-14) | 60 | Not verifiedUnverified |
| Artificial Analysis Intelligence Index (2026-08-14) | Not verifiedUnverified | 52 |
| Terminal-Bench 2.1 (2026-08-14) | 88.2 | Not verifiedUnverified |
| DeepSWE 1.1 (2026-08-14) | 66.9 | Not verifiedUnverified |
| Humanity's Last Exam (2026-08-14) | 62.5 | Not verifiedUnverified |
| SWE-bench Verified (2026-09-01) | 95.4 | Not verifiedUnverified |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Benchmark receipts
- 2026-09-01: vals.ai SWE-bench Verified leaderboard (independent, mini-swe-agent bash-only); Zhipu docs list 77.8 inherited from GLM-5 — attribution contested, both notedReal GitHub issue resolution: does the model's patch pass the hidden tests. Comparability: comparable with caveat — Post-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.
- 2026-08-14: Z.ai GLM-5.3 blog + HF model card (vendor, with tools, full set)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
- 2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
Pricing tiers: GLM 5.3: Token API listed at $1.40/$4.40 per MTok from 2026-08-18 (cached input $0.26); Coding Plan access on a points quota. 1M context, 128K max output per official docs; thinking always on. 753B total MoE per the Hugging Face card (active count unpublished). · Qwen3-Max: Qwen API $1.20/$6.00 per MTok (≤32K); higher tiers for 32K–256K. OpenRouter lists ~$0.78/$3.90. Proprietary, API-only.
GLM 5.3
GLM 5.3 is Zhipu's flagship (~753B MoE), near the top of the leaderboards, and the current GLM Coding Plan default.
Best for
- Coding Plan subscribers
- Long-horizon coding
- Chinese + English
Watch out
Open weights dropped 2026-08-28 under Z.ai's custom glm-5.3 licence (not a standard open-source licence — review before commercial use; secondary coverage says >$10B-revenue providers need a security review). 5.2/5.1 Coding Plan requests route to 5.3.
Qwen3-Max
Qwen3-Max is Alibaba's proprietary 1-trillion-parameter API model with multimodal input.
Best for
- Agentic coding
- Multimodal knowledge work
- Long-context via API
Watch out
Max line is proprietary/API-only (no published weights). Per-provider prices differ.
When the cheaper one wins
GLM 5.3 is cheaper on output at $4.40 per million tokens against $6 for Qwen3-Max — about 1.4×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.
Run the model pickerEvidence confidence: High
How strong and complete the evidence behind this comparison is — not a prediction of which model is better.
- Pricing verified on both sides — Input and output rates are verified for both models.
- 5/5 core specs verified on both sides — All core specifications verified for both models.
- 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
- Verified within the last 90 days — Newest catalog check was 8 days ago.
- Both models carry source citations — Each side has at least two catalog sources on record.
Source receipts
Each catalog figure was checked against the provider or an independent second source on the date shown.
- GLM 5.3: Z.ai GLM-5.3 announcement (accessed 2026-08-29)
- GLM 5.3: Hugging Face — zai-org/GLM-5.3 (weights, 2026-08-28) (accessed 2026-08-30)
- Qwen3-Max: OpenRouter — Qwen3-Max (accessed 2026-08-29)
- Qwen3-Max: AI Release Tracker — Qwen3-Max (accessed 2026-08-29)
Related comparisons
Common questions
GLM 5.3 vs Qwen3-Max
Answered from the verified figures on this page rather than general guidance.
Is GLM 5.3 or Qwen3-Max cheaper for input?
Qwen3-Max is cheaper at $1.20 per million input tokens, against $1.40 for GLM 5.3 — roughly 1.2× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; GLM 5.3 has tiered pricing: Token API listed at $1.40/$4.40 per MTok from 2026-08-18 (cached input $0.26); Coding Plan access on a points quota. 1M context, 128K max output per official docs; thinking always on. 753B total MoE per the Hugging Face card (active count unpublished). Qwen3-Max has tiered pricing: Qwen API $1.20/$6.00 per MTok (≤32K); higher tiers for 32K–256K. OpenRouter lists ~$0.78/$3.90. Proprietary, API-only.
Is GLM 5.3 or Qwen3-Max cheaper for output?
GLM 5.3 is cheaper at $4.40 per million output tokens, against $6 for Qwen3-Max — roughly 1.4× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; GLM 5.3 has tiered pricing: Token API listed at $1.40/$4.40 per MTok from 2026-08-18 (cached input $0.26); Coding Plan access on a points quota. 1M context, 128K max output per official docs; thinking always on. 753B total MoE per the Hugging Face card (active count unpublished). Qwen3-Max has tiered pricing: Qwen API $1.20/$6.00 per MTok (≤32K); higher tiers for 32K–256K. OpenRouter lists ~$0.78/$3.90. Proprietary, API-only.
Which has the larger context window, GLM 5.3 or Qwen3-Max?
GLM 5.3 accepts 1M tokens against 262K for Qwen3-Max. This only matters if you routinely send very long documents or large codebases.
Do GLM 5.3 and Qwen3-Max support the same reasoning levels?
Yes — both accept the same effort settings: "low", "high", "max". Higher effort costs more and takes longer, so start low and raise it only where output quality actually improves.
Should I use GLM 5.3 or Qwen3-Max?
Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. GLM 5.3 suits coding plan subscribers; Qwen3-Max suits agentic coding.
Can I self-host GLM 5.3 or Qwen3-Max?
GLM 5.3 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Qwen3-Max is a closed model whose supported access paths are controlled by its provider.
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: Qwen3-Max costs $1.20 per 1M tokens versus $1.40 for GLM 5.3 — a 1.2x difference at the headline tier.
- Context: GLM 5.3 takes 1M against 262K for Qwen3-Max — only decisive if your prompts approach the smaller window.
- Measured capability: GLM 5.3 leads Artificial Analysis Intelligence Index 60 to 52 (measured 2026-08-14).
- Deployment: GLM 5.3 publishes weights you can self-host; the other is API-only.
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