Grok 4.6 vs GLM-5.3 vs Qwen3.8 Max
Qwen3.8 Max comes out ahead, 69 to 65 and 64 on our weighted score, though GLM-5.3 is 28% cheaper per token.
xAIGrok 4.6
65/100- ECI156.6
- Price$2.00 / $6.00
- Context500K
Z.ai (Zhipu)GLM-5.3
64/100- ECI155.8
- Price$1.40 / $4.40
- Context1M
- Our pick
Alibaba (Qwen)Qwen3.8 Max
69/100- ECI156.6
- Price$2.00 / $6.00
- Context1M
Qwen3.8 Max is our pick
Qwen3.8 Max is the better all-round choice, scoring 69/100 against Grok 4.6 (65) and GLM-5.3 (64). It leads on inputs & features. GLM-5.3 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGrok 4.6Capabilities Index (ECI): Grok 4.6 156.6 · Qwen3.8 Max 156.6 · GLM-5.3 155.8
- Lowest priceGLM-5.3GLM-5.3 $2.15 · Grok 4.6 $3.00 · Qwen3.8 Max $3.00 per 1M tokens (3:1 blend)
- Longest contextGLM-5.3 and Qwen3.8 MaxGLM-5.3 1,000,000 · Qwen3.8 Max 1,000,000 · Grok 4.6 500,000 tokens
- Widest inputsQwen3.8 MaxGrok 4.6: Text, Images · GLM-5.3: Text · Qwen3.8 Max: Text, Images, PDFs, Video
- Self-hostingGLM-5.3Publishes downloadable weights
| Measure | Weight | Grok 4.6 | GLM-5.3 | Qwen3.8 Max |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 86 | 85 | 86 |
| Price | 25% | 27 | 34 | 27 |
| Inputs & features | 15% | 70 | 45 | 90 |
| Context window | 10% | 48 | 60 | 60 |
| Overall | 100% | 65/100 | 64/100 | 69/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Grok 4.6xAI | GLM-5.3Z.ai (Zhipu) | Qwen3.8 MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.6 (best) | 155.8 | 156.6 |
| ECI rank | #19 of 148 (best) | #24 of 148 | #20 of 148 |
| GPQA DiamondGraduate-level science questions | 94.0% (best) | 90.9% | 92.7% |
| FrontierMath Tiers 1–3Research-level mathematics | 66.0% | 68.8% | 74.7% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 99.2% | 91.1% | 99.4% (best) |
| SimpleQA VerifiedShort factual questions | 49.3% (best) | 41.0% | 45.8% |
| Price per million tokens | |||
| Input | $2.00 | $1.40 (best) | $2.00 |
| Output | $6.00 | $4.40 (best) | $6.00 |
| Cached input | $0.50 | $0.26 | $0.25 (best) |
| Blended (3:1) | $3.00 | $2.15 (best) | $3.00 |
| Long-context rate | Over 200K: $4.00 / $12.00 | Same rate | Same rate |
| Price source | Official xAI API | Official Z.AI API | Official Alibaba API |
| Limits | |||
| Context window | 500,000 tokens | 1,000,000 tokens (best) | 1,000,000 tokens (best) |
| Max output | 500,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yeslow · medium · high · xhigh | Yeslow · high · max | Yeslow · medium · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | grok-4.6 | glm-5.3 | qwen3.8-max |
| API providers | 29 | 62 (best) | 25 |
| Released | Aug 12, 2026 | Aug 14, 2026 | Aug 3, 2026 |
| Knowledge cutoff | Feb 1, 2026 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Grok 4.6$32.00
- GLM-5.3$22.80
- Qwen3.8 Max$32.00
Which should you choose?
Which is better: Grok 4.6, GLM-5.3 or Qwen3.8 Max?
Qwen3.8 Max is the better all-round choice, scoring 69/100 against Grok 4.6 (65) and GLM-5.3 (64). It leads on inputs & features. GLM-5.3 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Grok 4.6, GLM-5.3 or Qwen3.8 Max?
GLM-5.3 is cheaper at $1.40 input / $4.40 output per million tokens (official Z.AI API price). Grok 4.6 costs $2.00 input / $6.00 output per million tokens (official xAI API price); Qwen3.8 Max costs $2.00 input / $6.00 output per million tokens (official Alibaba API price). At a typical mix of three input tokens to one output token, that is $2.15 per million tokens for GLM-5.3 versus $3.00 for Grok 4.6 (1.4× as much) and $3.00 for Qwen3.8 Max (1.4× as much).
Which scores higher on benchmarks?
Grok 4.6 scores higher on the Capabilities Index (ECI): Grok 4.6 156.6 (#19 of 148), Qwen3.8 Max 156.6 (#20 of 148) and GLM-5.3 155.8 (#24 of 148). The confidence ranges of the top two overlap (154.7–158.9 vs 154.5–158.8), so treat the gap as small. On individual benchmarks: GPQA Diamond — Grok 4.6 94.0%, Qwen3.8 Max 92.7%, GLM-5.3 90.9%; FrontierMath Tiers 1–3 — Qwen3.8 Max 74.7%, GLM-5.3 68.8%, Grok 4.6 66.0%; OTIS Mock AIME 2024–2025 — Qwen3.8 Max 99.4%, Grok 4.6 99.2%, GLM-5.3 91.1%; SimpleQA Verified — Grok 4.6 49.3%, Qwen3.8 Max 45.8%, GLM-5.3 41.0%.
Which is better for coding?
There are no published SWE-bench Verified results for Grok 4.6, GLM-5.3 and Qwen3.8 Max yet, so there is no like-for-like coding score. On overall capability, Grok 4.6 leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
GLM-5.3 and Qwen3.8 Max have the largest context windows (1,000,000 and 1,000,000 tokens), against 500,000 for Grok 4.6. Maximum output per response: Grok 4.6 up to 500,000, GLM-5.3 up to 131,072, Qwen3.8 Max up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Grok 4.6 accepts text and images; GLM-5.3 accepts text; Qwen3.8 Max accepts text, images, PDFs and video. Qwen3.8 Max handles the widest range of inputs.
Are any of these open source?
GLM-5.3 publishes its weights and can be self-hosted; Grok 4.6 and Qwen3.8 Max is proprietary.
Which is newer?
GLM-5.3 is the newest, released Aug 14, 2026. Grok 4.6 came out Aug 12, 2026; Qwen3.8 Max came out Aug 3, 2026. Knowledge cutoff: Grok 4.6 Feb 1, 2026.
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.
