GLM-5.1 vs GPT-5.3 Codex vs Qwen3.6 Max Preview
GPT-5.3 Codex comes out ahead, 64 to 57 and 54 on our weighted score, though GLM-5.1 is 2.2× cheaper per token.
Z.ai (Zhipu)GLM-5.1
57/100- ECI149.9
- Price$1.40 / $4.40
- Context200K
- Our pick
OpenAIGPT-5.3 Codex
64/100- ECI156.8
- Price$1.75 / $14.00
- Context400K
Alibaba (Qwen)Qwen3.6 Max Preview
54/100- ECI149.2
- Price$1.30 / $7.80
- Context262K
GPT-5.3 Codex is our pick
GPT-5.3 Codex is the better all-round choice, scoring 64/100 against GLM-5.1 (57) and Qwen3.6 Max Preview (54). It leads on capability, inputs & features and context window. GLM-5.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.3 CodexCapabilities Index (ECI): GPT-5.3 Codex 156.8 · GLM-5.1 149.9 · Qwen3.6 Max Preview 149.2
- Lowest priceGLM-5.1GLM-5.1 $2.15 · Qwen3.6 Max Preview $2.92 · GPT-5.3 Codex $4.81 per 1M tokens (3:1 blend)
- Longest contextGPT-5.3 CodexGPT-5.3 Codex 400,000 · Qwen3.6 Max Preview 262,144 · GLM-5.1 200,000 tokens
- Widest inputsGPT-5.3 CodexGLM-5.1: Text · GPT-5.3 Codex: Text, Images, PDFs · Qwen3.6 Max Preview: Text
- Self-hostingGLM-5.1Publishes downloadable weights
| Measure | Weight | GLM-5.1 | GPT-5.3 Codex | Qwen3.6 Max Preview |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 78 | 87 | 77 |
| Price | 25% | 34 | 18 | 28 |
| Inputs & features | 15% | 45 | 80 | 35 |
| Context window | 10% | 32 | 44 | 37 |
| Overall | 100% | 57/100 | 64/100 | 54/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | GLM-5.1Z.ai (Zhipu) | GPT-5.3 CodexOpenAI | Qwen3.6 Max PreviewAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 149.9 | 156.8 (best) | 149.2 |
| ECI rank | #51 of 148 | #18 of 148 (best) | #54 of 148 |
| GPQA DiamondGraduate-level science questions | 89.9% (best) | — | 87.4% |
| FrontierMath Tiers 1–3Research-level mathematics | 36.8% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 93.3% (best) | — | 91.1% |
| SWE-bench VerifiedFixing real GitHub issues | 74.2% | 74.8% | 76.7% (best) |
| SimpleQA VerifiedShort factual questions | 34.0% | — | 52.0% (best) |
| Price per million tokens | |||
| Input | $1.40 | $1.75 | $1.30 (best) |
| Output | $4.40 (best) | $14.00 | $7.80 |
| Cached input | $0.26 | $0.175 | $0.13 (best) |
| Blended (3:1) | $2.15 (best) | $4.81 | $2.92 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official OpenAI API | Official Alibaba API |
| Limits | |||
| Context window | 200,000 tokens | 400,000 tokens (best) | 262,144 tokens |
| Max output | 131,072 tokens (best) | 128,000 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yeslow · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | glm-5.1 | gpt-5.3-codex | qwen3.6-max-preview |
| API providers | 40 (best) | 19 | 10 |
| Released | Apr 7, 2026 | Feb 5, 2026 | Apr 20, 2026 |
| Knowledge cutoff | — | Aug 31, 2025 | Apr 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5.1$22.80
- GPT-5.3 Codex$45.50
- Qwen3.6 Max Preview$28.60
Which should you choose?
Which is better: GLM-5.1, GPT-5.3 Codex or Qwen3.6 Max Preview?
GPT-5.3 Codex is the better all-round choice, scoring 64/100 against GLM-5.1 (57) and Qwen3.6 Max Preview (54). It leads on capability, inputs & features and context window. GLM-5.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, GLM-5.1, GPT-5.3 Codex or Qwen3.6 Max Preview?
GLM-5.1 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI API price). Qwen3.6 Max Preview costs $1.30 input / $7.80 output per million tokens (official Alibaba API price); GPT-5.3 Codex costs $1.75 input / $14.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $2.15 per million tokens for GLM-5.1 versus $2.92 for Qwen3.6 Max Preview (1.4× as much) and $4.81 for GPT-5.3 Codex (2.2× as much).
Which scores higher on benchmarks?
GPT-5.3 Codex scores higher on the Capabilities Index (ECI): GPT-5.3 Codex 156.8 (#18 of 148), GLM-5.1 149.9 (#51 of 148) and Qwen3.6 Max Preview 149.2 (#54 of 148). Their confidence ranges do not overlap (153.5–160.8 vs 148.0–151.6), so the gap is a real one. On individual benchmarks: SWE-bench Verified — Qwen3.6 Max Preview 76.7%, GPT-5.3 Codex 74.8%, GLM-5.1 74.2%.
Which is better for coding?
Qwen3.6 Max Preview resolves more real GitHub issues on SWE-bench Verified: Qwen3.6 Max Preview 76.7%, GPT-5.3 Codex 74.8% and GLM-5.1 74.2%. All three support tool calling for agent workflows.
Which has the bigger context window?
GPT-5.3 Codex has the largest context window at 400,000 tokens, against 262,144 for Qwen3.6 Max Preview and 200,000 for GLM-5.1. Maximum output per response: GLM-5.1 up to 131,072, GPT-5.3 Codex up to 128,000, Qwen3.6 Max Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-5.1 accepts text; GPT-5.3 Codex accepts text, images and PDFs; Qwen3.6 Max Preview accepts text. GPT-5.3 Codex handles the widest range of inputs.
Are any of these open source?
GLM-5.1 publishes its weights and can be self-hosted; GPT-5.3 Codex and Qwen3.6 Max Preview is proprietary.
Which is newer?
Qwen3.6 Max Preview is the newest, released Apr 20, 2026. GLM-5.1 came out Apr 7, 2026; GPT-5.3 Codex came out Feb 5, 2026. Knowledge cutoff: GPT-5.3 Codex Aug 31, 2025, Qwen3.6 Max Preview Apr 2025.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
