Qwen3 235B-A22B Thinking 2507 vs Grok 4 Fast Non Reasoning vs GLM-4.7
Grok 4 Fast Non Reasoning comes out ahead, 72 to 42 and 41 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3 235B-A22B Thinking 2507
42/100- ECI143.8
- Price$0.30 / $2.90
- Context262K
- Our pick
xAIGrok 4 Fast Non Reasoning
72/100- ECI—
- Price$0.20 / $0.50
- Context2M
Z.ai (Zhipu)GLM-4.7
41/100- ECI143.7
- Price$0.60 / $2.20
- Context205K
Grok 4 Fast Non Reasoning is our pick
Grok 4 Fast Non Reasoning is the better all-round choice, scoring 72/100 against Qwen3 235B-A22B Thinking 2507 (42) and GLM-4.7 (41). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceGrok 4 Fast Non ReasoningGrok 4 Fast Non Reasoning $0.275 · Qwen3 235B-A22B Thinking 2507 $0.95 · GLM-4.7 $1.00 per 1M tokens (3:1 blend)
- Longest contextGrok 4 Fast Non ReasoningGrok 4 Fast Non Reasoning 2,000,000 · Qwen3 235B-A22B Thinking 2507 262,144 · GLM-4.7 204,800 tokens
- Widest inputsGrok 4 Fast Non ReasoningQwen3 235B-A22B Thinking 2507: Text · Grok 4 Fast Non Reasoning: Text, Images, Audio, Video · GLM-4.7: Text
- Self-hostingQwen3 235B-A22B Thinking 2507 and GLM-4.7Publishes downloadable weights (Apache 2.0)
| Measure | Weight | Qwen3 235B-A22B Thinking 2507 | Grok 4 Fast Non Reasoning | GLM-4.7 |
|---|---|---|---|---|
| Price | 50% | 49 | 73 | 48 |
| Inputs & features | 30% | 35 | 70 | 35 |
| Context window | 20% | 37 | 72 | 32 |
| Overall | 100% | 42/100 | 72/100 | 41/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Qwen3 235B-A22B Thinking 2507Alibaba (Qwen) | Grok 4 Fast Non ReasoningxAI | GLM-4.7Z.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 143.8 (best) | — | 143.7 |
| ECI rank | #93 of 165 (best) | — | #94 of 165 |
| GPQA DiamondGraduate-level science questions | 80.1% | — | 83.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 86.7% (best) | — | 83.3% |
| SimpleQA VerifiedShort factual questions | 40.4% (best) | — | 32.2% |
| Price per million tokens | |||
| Input | $0.30 | $0.20 (best) | $0.60 |
| Output | $2.90 | $0.50 (best) | $2.20 |
| Cached input | — | — | $0.11 |
| Blended (3:1) | $0.95 | $0.275 (best) | $1.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 11 providers | Median of 7 providers | Official Z.AI API |
| Limits | |||
| Context window | 262,144 tokens | 2,000,000 tokens (best) | 204,800 tokens |
| Max output | 81,920 tokens | 2,000,000 tokens (best) | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | No |
| PDFs | No | No | No |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenApache 2.0 | Proprietary | Open |
| API model ID | — | — | glm-4.7 |
| API providers | 12 | 8 | 31 (best) |
| Released | Jul 25, 2025 | Dec 18, 2025 | Dec 22, 2025 |
| Knowledge cutoff | — | — | 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.
- Qwen3 235B-A22B Thinking 2507$8.80
- Grok 4 Fast Non Reasoning$3.00
- GLM-4.7$10.40
Which should you choose?
Which is better: Qwen3 235B-A22B Thinking 2507, Grok 4 Fast Non Reasoning or GLM-4.7?
Grok 4 Fast Non Reasoning is the better all-round choice, scoring 72/100 against Qwen3 235B-A22B Thinking 2507 (42) and GLM-4.7 (41). It leads on price, inputs & features and context window. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Qwen3 235B-A22B Thinking 2507, Grok 4 Fast Non Reasoning or GLM-4.7?
Grok 4 Fast Non Reasoning is cheaper at $0.20 input / $0.50 output per million tokens (median across 7 API providers). Qwen3 235B-A22B Thinking 2507 costs $0.30 input / $2.90 output per million tokens (median across 11 API providers); GLM-4.7 costs $0.60 input / $2.20 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.275 per million tokens for Grok 4 Fast Non Reasoning versus $0.95 for Qwen3 235B-A22B Thinking 2507 (3.5× as much) and $1.00 for GLM-4.7 (3.6× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3 235B-A22B Thinking 2507 has an ECI of 143.8, Grok 4 Fast Non Reasoning has not been scored yet and GLM-4.7 has an ECI of 143.7.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3 235B-A22B Thinking 2507, Grok 4 Fast Non Reasoning and GLM-4.7 yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Grok 4 Fast Non Reasoning has the largest context window at 2,000,000 tokens, against 262,144 for Qwen3 235B-A22B Thinking 2507 and 204,800 for GLM-4.7. Maximum output per response: Qwen3 235B-A22B Thinking 2507 up to 81,920, Grok 4 Fast Non Reasoning up to 2,000,000, GLM-4.7 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Qwen3 235B-A22B Thinking 2507 accepts text; Grok 4 Fast Non Reasoning accepts text, images, audio and video; GLM-4.7 accepts text. Grok 4 Fast Non Reasoning handles the widest range of inputs.
Are any of these open source?
Qwen3 235B-A22B Thinking 2507 and GLM-4.7 publishes its weights (Apache 2.0) and can be self-hosted; Grok 4 Fast Non Reasoning is proprietary.
Which is newer?
GLM-4.7 is the newest, released Dec 22, 2025. Grok 4 Fast Non Reasoning came out Dec 18, 2025; Qwen3 235B-A22B Thinking 2507 came out Jul 25, 2025. Knowledge cutoff: GLM-4.7 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 Nov 2, 2026.
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