Gemini 3.5 Flash vs Muse Spark 1.2 vs Qwen3.7 Max
Muse Spark 1.2 comes out ahead, 72 to 69 and 58 on our weighted score, and it is the cheaper option too.
GoogleGemini 3.5 Flash
69/100- ECI154.5
- Price$1.50 / $9.00
- Context1.05M
- Our pick
MetaMuse Spark 1.2
72/100- ECI155.0
- Price$1.25 / $4.25
- Context1.05M
Alibaba (Qwen)Qwen3.7 Max
58/100- ECI153.7
- Price$2.50 / $7.50
- Context1M
Muse Spark 1.2 is our pick
Muse Spark 1.2 is the better all-round choice, scoring 72/100 against Gemini 3.5 Flash (69) and Qwen3.7 Max (58). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMuse Spark 1.2Capabilities Index (ECI): Muse Spark 1.2 155.0 · Gemini 3.5 Flash 154.5 · Qwen3.7 Max 153.7
- Lowest priceMuse Spark 1.2Muse Spark 1.2 $2.00 · Gemini 3.5 Flash $3.38 · Qwen3.7 Max $3.75 per 1M tokens (3:1 blend)
- Longest contextGemini 3.5 Flash and Muse Spark 1.2Gemini 3.5 Flash 1,048,576 · Muse Spark 1.2 1,048,576 · Qwen3.7 Max 1,000,000 tokens
- Widest inputsGemini 3.5 Flash and Muse Spark 1.2Gemini 3.5 Flash: Text, Images, PDFs, Audio, Video · Muse Spark 1.2: Text, Images, PDFs, Audio, Video · Qwen3.7 Max: Text
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Gemini 3.5 Flash | Muse Spark 1.2 | Qwen3.7 Max |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 84 | 83 |
| Price | 25% | 25 | 36 | 23 |
| Inputs & features | 15% | 100 | 100 | 35 |
| Context window | 10% | 61 | 61 | 60 |
| Overall | 100% | 69/100 | 72/100 | 58/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 3.5 FlashGoogle | Muse Spark 1.2Meta | Qwen3.7 MaxAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 154.5 | 155.0 (best) | 153.7 |
| ECI rank | #33 of 148 | #30 of 148 (best) | #37 of 148 |
| GPQA DiamondGraduate-level science questions | 92.8% (best) | — | 90.9% |
| FrontierMath Tiers 1–3Research-level mathematics | 62.8% | — | 64.6% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 95.6% | — | 95.6% |
| SWE-bench VerifiedFixing real GitHub issues | 79.3% (best) | — | 77.3% |
| SimpleQA VerifiedShort factual questions | 66.2% (best) | 60.3% | 55.8% |
| Price per million tokens | |||
| Input | $1.50 | $1.25 (best) | $2.50 |
| Output | $9.00 | $4.25 (best) | $7.50 |
| Cached input | $0.15 (best) | $0.15 (best) | $0.50 |
| Blended (3:1) | $3.38 | $2.00 (best) | $3.75 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Official Meta API | Official Alibaba API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,048,576 tokens (best) | 1,000,000 tokens |
| Max output | 65,536 tokens | 131,072 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | Yes | No |
| Audio | Yes | Yes | No |
| Video | Yes | Yes | No |
| Reasoning | Yesminimal · low · medium · high | Yesminimal · low · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gemini-3.5-flash | muse-spark-1.2 | qwen3.7-max |
| API providers | 32 (best) | 15 | 26 |
| Released | May 19, 2026 | Aug 5, 2026 | May 21, 2026 |
| Knowledge cutoff | Jan 2025 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 3.5 Flash$33.00
- Muse Spark 1.2$21.00
- Qwen3.7 Max$40.00
Which should you choose?
Which is better: Gemini 3.5 Flash, Muse Spark 1.2 or Qwen3.7 Max?
Muse Spark 1.2 is the better all-round choice, scoring 72/100 against Gemini 3.5 Flash (69) and Qwen3.7 Max (58). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 3.5 Flash, Muse Spark 1.2 or Qwen3.7 Max?
Muse Spark 1.2 is cheaper at $1.25 input / $4.25 output per million tokens (official Meta API price). Gemini 3.5 Flash costs $1.50 input / $9.00 output per million tokens (official Google API price); Qwen3.7 Max costs $2.50 input / $7.50 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 1.2 versus $3.38 for Gemini 3.5 Flash (1.7× as much) and $3.75 for Qwen3.7 Max (1.9× as much).
Which scores higher on benchmarks?
Muse Spark 1.2 scores higher on the Capabilities Index (ECI): Muse Spark 1.2 155.0 (#30 of 148), Gemini 3.5 Flash 154.5 (#33 of 148) and Qwen3.7 Max 153.7 (#37 of 148). The confidence ranges of the top two overlap (152.8–157.5 vs 152.5–156.6), so treat the gap as small. On individual benchmarks: SimpleQA Verified — Gemini 3.5 Flash 66.2%, Muse Spark 1.2 60.3%, Qwen3.7 Max 55.8%.
Which is better for coding?
There are no published SWE-bench Verified results for Muse Spark 1.2 yet, so there is no like-for-like coding score. On overall capability, Muse Spark 1.2 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?
Gemini 3.5 Flash and Muse Spark 1.2 have the largest context windows (1,048,576 and 1,048,576 tokens), against 1,000,000 for Qwen3.7 Max. Maximum output per response: Gemini 3.5 Flash up to 65,536, Muse Spark 1.2 up to 131,072, Qwen3.7 Max up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemini 3.5 Flash accepts text, images, PDFs, audio and video; Muse Spark 1.2 accepts text, images, PDFs, audio and video; Qwen3.7 Max accepts text. Gemini 3.5 Flash handles the widest range of inputs.
Are any of these open source?
No. Gemini 3.5 Flash, Muse Spark 1.2 and Qwen3.7 Max are proprietary and only available through APIs and apps.
Which is newer?
Muse Spark 1.2 is the newest, released Aug 5, 2026. Qwen3.7 Max came out May 21, 2026; Gemini 3.5 Flash came out May 19, 2026. Knowledge cutoff: Gemini 3.5 Flash Jan 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 Oct 4, 2026.
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