Grok 4.7 vs Qwen3.8 Flash vs Qwen3.8 Max 0902
Qwen3.8 Flash comes out ahead, 76 to 50 and 47 on our weighted score, and it is the cheaper option too.
xAIGrok 4.7
47/100- ECI—
- Price$2.00 / $6.00
- Context500K
- Our pick
Alibaba (Qwen)Qwen3.8 Flash
76/100- ECI—
- Price$0.15 / $0.47
- Context1M
- Alibaba (Qwen)
Qwen3.8 Max 0902
50/100- ECI155.2
- Price$2.00 / $6.00
- Context1M
Qwen3.8 Flash is our pick
Qwen3.8 Flash is the better all-round choice, scoring 76/100 against Qwen3.8 Max 0902 (50) and Grok 4.7 (47). It leads on price. 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 priceQwen3.8 FlashQwen3.8 Flash $0.23 · Grok 4.7 $3.00 · Qwen3.8 Max 0902 $3.00 per 1M tokens (3:1 blend)
- Longest contextQwen3.8 Flash and Qwen3.8 Max 0902Qwen3.8 Flash 1,000,000 · Qwen3.8 Max 0902 1,000,000 · Grok 4.7 500,000 tokens
- Widest inputsQwen3.8 Max 0902Grok 4.7: Text, Images, PDFs · Qwen3.8 Flash: Text, Images, Video · Qwen3.8 Max 0902: Text, Images, PDFs, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Grok 4.7 | Qwen3.8 Flash | Qwen3.8 Max 0902 |
|---|---|---|---|---|
| Price | 50% | 27 | 80 | 27 |
| Inputs & features | 30% | 80 | 80 | 80 |
| Context window | 20% | 48 | 60 | 60 |
| Overall | 100% | 47/100 | 76/100 | 50/100 |
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 | Grok 4.7xAI | Qwen3.8 FlashAlibaba (Qwen) | Qwen3.8 Max 0902Alibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | 155.2 |
| ECI rank | — | — | #28 of 148 |
| GPQA DiamondGraduate-level science questions | 92.7% (best) | — | 92.3% |
| FrontierMath Tiers 1–3Research-level mathematics | 53.0% | — | 65.6% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 98.1% | — | 100% (best) |
| SimpleQA VerifiedShort factual questions | 56.0% (best) | — | 47.3% |
| Price per million tokens | |||
| Input | $2.00 | $0.15 (best) | $2.00 |
| Output | $6.00 | $0.47 (best) | $6.00 |
| Cached input | $0.50 | $0.016 (best) | — |
| Blended (3:1) | $3.00 | $0.23 (best) | $3.00 |
| Long-context rate | Over 200K: $4.00 / $12.00 | Same rate | Same rate |
| Price source | Official xAI API | Official Alibaba API | Median of 6 providers |
| 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 | Yes | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | No | No |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · medium · high · xhigh | Yeslow · medium · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | grok-4.7 | qwen3.8-flash | — |
| API providers | 17 | 23 (best) | 6 |
| Released | Sep 21, 2026 | Aug 26, 2026 | Sep 2, 2026 |
| Knowledge cutoff | May 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 4.7$32.00
- Qwen3.8 Flash$2.44
- Qwen3.8 Max 0902$32.00
Which should you choose?
Which is better: Grok 4.7, Qwen3.8 Flash or Qwen3.8 Max 0902?
Qwen3.8 Flash is the better all-round choice, scoring 76/100 against Qwen3.8 Max 0902 (50) and Grok 4.7 (47). It leads on price. 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, Grok 4.7, Qwen3.8 Flash or Qwen3.8 Max 0902?
Qwen3.8 Flash is cheaper at $0.15 input / $0.47 output per million tokens (official Alibaba API price). Grok 4.7 costs $2.00 input / $6.00 output per million tokens (official xAI API price); Qwen3.8 Max 0902 costs $2.00 input / $6.00 output per million tokens (median across 6 API providers). At a typical mix of three input tokens to one output token, that is $0.23 per million tokens for Qwen3.8 Flash versus $3.00 for Grok 4.7 (13× as much) and $3.00 for Qwen3.8 Max 0902 (13× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Grok 4.7 has not been scored yet, Qwen3.8 Flash has not been scored yet and Qwen3.8 Max 0902 has an ECI of 155.2.
Which is better for coding?
There are no published SWE-bench Verified results for Grok 4.7, Qwen3.8 Flash and Qwen3.8 Max 0902 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?
Qwen3.8 Flash and Qwen3.8 Max 0902 have the largest context windows (1,000,000 and 1,000,000 tokens), against 500,000 for Grok 4.7. Maximum output per response: Grok 4.7 up to 500,000, Qwen3.8 Flash up to 131,072, Qwen3.8 Max 0902 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Grok 4.7 accepts text, images and PDFs; Qwen3.8 Flash accepts text, images and video; Qwen3.8 Max 0902 accepts text, images, PDFs and video. Qwen3.8 Max 0902 handles the widest range of inputs.
Are any of these open source?
No. Grok 4.7, Qwen3.8 Flash and Qwen3.8 Max 0902 are proprietary and only available through APIs and apps.
Which is newer?
Grok 4.7 is the newest, released Sep 21, 2026. Qwen3.8 Max 0902 came out Sep 2, 2026; Qwen3.8 Flash came out Aug 26, 2026. Knowledge cutoff: Grok 4.7 May 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.
