Qwen3.8 Max vs Qwen3.8 Flash vs Grok 4.6
Qwen3.8 Flash comes out ahead, 76 to 53 and 44 on our weighted score, and it is the cheaper option too.
Alibaba (Qwen)Qwen3.8 Max
53/100- ECI156.6
- Price$2.00 / $6.00
- Context1M
- Our pickAlibaba (Qwen)
Qwen3.8 Flash
76/100- ECI—
- Price$0.15 / $0.47
- Context1M
xAIGrok 4.6
44/100- ECI156.6
- Price$2.00 / $6.00
- Context500K
Qwen3.8 Flash is our pick
Qwen3.8 Flash is the better all-round choice, scoring 76/100 against Qwen3.8 Max (53) and Grok 4.6 (44). It leads on price. Qwen3.8 Max wins on inputs & features. 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 · Qwen3.8 Max $3.00 · Grok 4.6 $3.00 per 1M tokens (3:1 blend)
- Longest contextQwen3.8 Max and Qwen3.8 FlashQwen3.8 Max 1,000,000 · Qwen3.8 Flash 1,000,000 · Grok 4.6 500,000 tokens
- Widest inputsQwen3.8 MaxQwen3.8 Max: Text, Images, PDFs, Video · Qwen3.8 Flash: Text, Images, Video · Grok 4.6: Text, Images
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Qwen3.8 Max | Qwen3.8 Flash | Grok 4.6 |
|---|---|---|---|---|
| Price | 50% | 27 | 80 | 27 |
| Inputs & features | 30% | 90 | 80 | 70 |
| Context window | 20% | 60 | 60 | 48 |
| Overall | 100% | 53/100 | 76/100 | 44/100 |
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 | Qwen3.8 MaxAlibaba (Qwen) | Qwen3.8 FlashAlibaba (Qwen) | Grok 4.6xAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.6 | — | 156.6 (best) |
| ECI rank | #20 of 148 | — | #19 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 92.7% | — | 94.0% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 74.7% (best) | — | 66.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | 99.4% (best) | — | 99.2% |
| SimpleQA VerifiedShort factual questions | 45.8% | — | 49.3% (best) |
| Price per million tokens | |||
| Input | $2.00 | $0.15 (best) | $2.00 |
| Output | $6.00 | $0.47 (best) | $6.00 |
| Cached input | $0.25 | $0.016 (best) | $0.50 |
| Blended (3:1) | $3.00 | $0.23 (best) | $3.00 |
| Long-context rate | Same rate | Same rate | Over 200K: $4.00 / $12.00 |
| Price source | Official Alibaba API | Official Alibaba API | Official xAI API |
| Limits | |||
| Context window | 1,000,000 tokens (best) | 1,000,000 tokens (best) | 500,000 tokens |
| Max output | 131,072 tokens | 131,072 tokens | 500,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | Yes | Yes | No |
| Reasoning | Yeslow · medium · xhigh | Yeslow · medium · xhigh | Yeslow · medium · high · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | qwen3.8-max | qwen3.8-flash | grok-4.6 |
| API providers | 25 | 23 | 29 (best) |
| Released | Aug 3, 2026 | Aug 26, 2026 | Aug 12, 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.
- Qwen3.8 Max$32.00
- Qwen3.8 Flash$2.44
- Grok 4.6$32.00
Which should you choose?
Which is better: Qwen3.8 Max, Qwen3.8 Flash or Grok 4.6?
Qwen3.8 Flash is the better all-round choice, scoring 76/100 against Qwen3.8 Max (53) and Grok 4.6 (44). It leads on price. Qwen3.8 Max wins on inputs & features. 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, Qwen3.8 Max, Qwen3.8 Flash or Grok 4.6?
Qwen3.8 Flash is cheaper at $0.15 input / $0.47 output per million tokens (official Alibaba API price). Qwen3.8 Max costs $2.00 input / $6.00 output per million tokens (official Alibaba API price); Grok 4.6 costs $2.00 input / $6.00 output per million tokens (official xAI API price). 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 Qwen3.8 Max (13× as much) and $3.00 for Grok 4.6 (13× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Qwen3.8 Max has an ECI of 156.6, Qwen3.8 Flash has not been scored yet and Grok 4.6 has an ECI of 156.6.
Which is better for coding?
There are no published SWE-bench Verified results for Qwen3.8 Max, Qwen3.8 Flash and Grok 4.6 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 Max and Qwen3.8 Flash have the largest context windows (1,000,000 and 1,000,000 tokens), against 500,000 for Grok 4.6. Maximum output per response: Qwen3.8 Max up to 131,072, Qwen3.8 Flash up to 131,072, Grok 4.6 up to 500,000 tokens.
Which can read images, PDFs, audio or video?
Qwen3.8 Max accepts text, images, PDFs and video; Qwen3.8 Flash accepts text, images and video; Grok 4.6 accepts text and images. Qwen3.8 Max handles the widest range of inputs.
Are any of these open source?
No. Qwen3.8 Max, Qwen3.8 Flash and Grok 4.6 are proprietary and only available through APIs and apps.
Which is newer?
Qwen3.8 Flash is the newest, released Aug 26, 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.
