Grok 4.6 vs Muse Spark 1.1 vs Qwen3.8 Max
Too close to call on our weighted score (Muse Spark 1.1 70, Qwen3.8 Max 69, Grok 4.6 65). The right pick depends on what you value most.
xAIGrok 4.6
65/100- ECI156.6
- Price$2.00 / $6.00
- Context500K
MetaMuse Spark 1.1
70/100- ECI154.3
- Price$1.25 / $4.25
- Context1.05M
Alibaba (Qwen)Qwen3.8 Max
69/100- ECI156.6
- Price$2.00 / $6.00
- Context1M
Too close to call
It is close. Our weighted score puts them within a point (Muse Spark 1.1 70/100, Qwen3.8 Max 69/100, Grok 4.6 65/100), so choose by what matters most for your work: Grok 4.6 for raw capability, Muse Spark 1.1 on price and Muse Spark 1.1 for long inputs. 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 · Muse Spark 1.1 154.3
- Lowest priceMuse Spark 1.1Muse Spark 1.1 $2.00 · Grok 4.6 $3.00 · Qwen3.8 Max $3.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.1Muse Spark 1.1 1,048,576 · Qwen3.8 Max 1,000,000 · Grok 4.6 500,000 tokens
- Widest inputsMuse Spark 1.1 and Qwen3.8 MaxGrok 4.6: Text, Images · Muse Spark 1.1: Text, Images, PDFs, Video · Qwen3.8 Max: Text, Images, PDFs, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Grok 4.6 | Muse Spark 1.1 | Qwen3.8 Max |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 86 | 84 | 86 |
| Price | 25% | 27 | 36 | 27 |
| Inputs & features | 15% | 70 | 90 | 90 |
| Context window | 10% | 48 | 61 | 60 |
| Overall | 100% | 65/100 | 70/100 | 69/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Grok 4.6xAI | Muse Spark 1.1Meta | Qwen3.8 MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.6 (best) | 154.3 | 156.6 |
| ECI rank | #19 of 148 (best) | #35 of 148 | #20 of 148 |
| GPQA DiamondGraduate-level science questions | 94.0% (best) | — | 92.7% |
| FrontierMath Tiers 1–3Research-level mathematics | 66.0% | — | 74.7% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 99.2% | — | 99.4% (best) |
| SimpleQA VerifiedShort factual questions | 49.3% | 57.8% (best) | 45.8% |
| Price per million tokens | |||
| Input | $2.00 | $1.25 (best) | $2.00 |
| Output | $6.00 | $4.25 (best) | $6.00 |
| Cached input | $0.50 | $0.15 (best) | $0.25 |
| Blended (3:1) | $3.00 | $2.00 (best) | $3.00 |
| Long-context rate | Over 200K: $4.00 / $12.00 | Same rate | Same rate |
| Price source | Official xAI API | Official Meta API | Official Alibaba API |
| Limits | |||
| Context window | 500,000 tokens | 1,048,576 tokens (best) | 1,000,000 tokens |
| Max output | 500,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · medium · high · xhigh | Yesminimal · low · medium · high · xhigh | Yeslow · medium · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | grok-4.6 | muse-spark-1.1 | qwen3.8-max |
| API providers | 29 (best) | 13 | 25 |
| Released | Aug 12, 2026 | Jul 9, 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
- Muse Spark 1.1$21.00
- Qwen3.8 Max$32.00
Which should you choose?
Which is better: Grok 4.6, Muse Spark 1.1 or Qwen3.8 Max?
It is close. Our weighted score puts them within a point (Muse Spark 1.1 70/100, Qwen3.8 Max 69/100, Grok 4.6 65/100), so choose by what matters most for your work: Grok 4.6 for raw capability, Muse Spark 1.1 on price and Muse Spark 1.1 for long inputs. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Grok 4.6, Muse Spark 1.1 or Qwen3.8 Max?
Muse Spark 1.1 is cheaper at $1.25 input / $4.25 output per million tokens (official Meta 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 $2.00 per million tokens for Muse Spark 1.1 versus $3.00 for Grok 4.6 (1.5× as much) and $3.00 for Qwen3.8 Max (1.5× 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 Muse Spark 1.1 154.3 (#35 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: SimpleQA Verified — Muse Spark 1.1 57.8%, Grok 4.6 49.3%, Qwen3.8 Max 45.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Grok 4.6, Muse Spark 1.1 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?
Muse Spark 1.1 has the largest context window at 1,048,576 tokens, against 1,000,000 for Qwen3.8 Max and 500,000 for Grok 4.6. Maximum output per response: Grok 4.6 up to 500,000, Muse Spark 1.1 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; Muse Spark 1.1 accepts text, images, PDFs and video; Qwen3.8 Max accepts text, images, PDFs and video. Muse Spark 1.1 handles the widest range of inputs.
Are any of these open source?
No. Grok 4.6, Muse Spark 1.1 and Qwen3.8 Max are proprietary and only available through APIs and apps.
Which is newer?
Grok 4.6 is the newest, released Aug 12, 2026. Qwen3.8 Max came out Aug 3, 2026; Muse Spark 1.1 came out Jul 9, 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.
