Muse Spark 1.1 vs Qwen3.8 27B vs Gemini 3.6 Flash
Gemini 3.6 Flash comes out ahead, 72 to 69 and 66 on our weighted score, though Qwen3.8 27B is 38% cheaper per token.
MetaMuse Spark 1.1
69/100- ECI154.2
- Price$1.25 / $4.25
- Context1.05M
Alibaba (Qwen)Qwen3.8 27B
66/100- ECI151.8
- Price$0.40 / $2.55
- Context262K
- Our pick
GoogleGemini 3.6 Flash
72/100- ECI154.7
- Price$0.75 / $3.75
- Context1.05M
Gemini 3.6 Flash is our pick
Gemini 3.6 Flash is the better all-round choice, scoring 72/100 against Muse Spark 1.1 (69) and Qwen3.8 27B (66). It leads on inputs & features. Qwen3.8 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemini 3.6 FlashCapabilities Index (ECI): Gemini 3.6 Flash 154.7 · Muse Spark 1.1 154.2 · Qwen3.8 27B 151.8
- Lowest priceQwen3.8 27BQwen3.8 27B $0.938 · Gemini 3.6 Flash $1.50 · Muse Spark 1.1 $2.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.1 and Gemini 3.6 FlashMuse Spark 1.1 1,048,576 · Gemini 3.6 Flash 1,048,576 · Qwen3.8 27B 262,144 tokens
- Widest inputsGemini 3.6 FlashMuse Spark 1.1: Text, Images, PDFs, Video · Qwen3.8 27B: Text, Images, Video · Gemini 3.6 Flash: Text, Images, PDFs, Audio, Video
- Self-hostingQwen3.8 27BPublishes downloadable weights
| Measure | Weight | Muse Spark 1.1 | Qwen3.8 27B | Gemini 3.6 Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 82 | 79 | 82 |
| Price | 25% | 34 | 49 | 40 |
| Inputs & features | 15% | 90 | 70 | 100 |
| Context window | 10% | 61 | 37 | 61 |
| Overall | 100% | 69/100 | 66/100 | 72/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Muse Spark 1.1Meta | Qwen3.8 27BAlibaba (Qwen) | Gemini 3.6 FlashGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 154.2 | 151.8 | 154.7 (best) |
| ECI rank | #46 of 165 | #54 of 165 | #42 of 165 (best) |
| GPQA DiamondGraduate-level science questions | — | — | 94.1% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 59.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 94.2% |
| SimpleQA VerifiedShort factual questions | 57.8% | — | 66.2% (best) |
| Price per million tokens | |||
| Input | $1.25 | $0.40 (best) | $0.75 |
| Output | $4.25 | $2.55 (best) | $3.75 |
| Cached input | $0.15 | — | $0.075 (best) |
| Blended (3:1) | $2.00 | $0.938 (best) | $1.50 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Meta API | Median of 49 providers | Official Google API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 1,048,576 tokens (best) |
| Max output | 131,072 tokens (best) | 32,768 tokens | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | Yes |
| Audio | No | No | Yes |
| Video | Yes | Yes | Yes |
| Reasoning | Yesminimal · low · medium · high · xhigh | Yes | Yesminimal · low · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | muse-spark-1.1 | — | gemini-3.6-flash |
| API providers | 15 | 53 (best) | 31 |
| Released | Jul 9, 2026 | Aug 14, 2026 | Jul 21, 2026 |
| Knowledge cutoff | — | — | Mar 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Muse Spark 1.1$21.00
- Qwen3.8 27B$9.10
- Gemini 3.6 Flash$15.00
Which should you choose?
Which is better: Muse Spark 1.1, Qwen3.8 27B or Gemini 3.6 Flash?
Gemini 3.6 Flash is the better all-round choice, scoring 72/100 against Muse Spark 1.1 (69) and Qwen3.8 27B (66). It leads on inputs & features. Qwen3.8 27B wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Muse Spark 1.1, Qwen3.8 27B or Gemini 3.6 Flash?
Qwen3.8 27B is cheaper at $0.40 input / $2.55 output per million tokens (median across 49 API providers). Gemini 3.6 Flash costs $0.75 input / $3.75 output per million tokens (official Google API price); Muse Spark 1.1 costs $1.25 input / $4.25 output per million tokens (official Meta API price). At a typical mix of three input tokens to one output token, that is $0.938 per million tokens for Qwen3.8 27B versus $1.50 for Gemini 3.6 Flash (1.6× as much) and $2.00 for Muse Spark 1.1 (2.1× as much).
Which scores higher on benchmarks?
Gemini 3.6 Flash scores higher on the Capabilities Index (ECI): Gemini 3.6 Flash 154.7 (#42 of 165), Muse Spark 1.1 154.2 (#46 of 165) and Qwen3.8 27B 151.8 (#54 of 165). The confidence ranges of the top two overlap (153.0–156.7 vs 151.3–156.4), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Muse Spark 1.1, Qwen3.8 27B and Gemini 3.6 Flash yet, so there is no like-for-like coding score. On overall capability, Gemini 3.6 Flash 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 and Gemini 3.6 Flash have the largest context windows (1,048,576 and 1,048,576 tokens), against 262,144 for Qwen3.8 27B. Maximum output per response: Muse Spark 1.1 up to 131,072, Qwen3.8 27B up to 32,768, Gemini 3.6 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Muse Spark 1.1 accepts text, images, PDFs and video; Qwen3.8 27B accepts text, images and video; Gemini 3.6 Flash accepts text, images, PDFs, audio and video. Gemini 3.6 Flash handles the widest range of inputs.
Are any of these open source?
Qwen3.8 27B publishes its weights and can be self-hosted; Muse Spark 1.1 and Gemini 3.6 Flash is proprietary.
Which is newer?
Qwen3.8 27B is the newest, released Aug 14, 2026. Gemini 3.6 Flash came out Jul 21, 2026; Muse Spark 1.1 came out Jul 9, 2026. Knowledge cutoff: Gemini 3.6 Flash Mar 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 Nov 2, 2026.
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