Muse Spark 1.3 vs Muse Spark 1.1 vs Gemini 3.8 Flash
Too close to call on our weighted score (Gemini 3.8 Flash 75, Muse Spark 1.3 73, Muse Spark 1.1 70). The right pick depends on what you value most.
MetaMuse Spark 1.3
73/100- ECI156.9
- Price$1.25 / $4.25
- Context1.05M
- Meta
Muse Spark 1.1
70/100- ECI154.3
- Price$1.25 / $4.25
- Context1.05M
GoogleGemini 3.8 Flash
75/100- ECI156.9
- Price$0.75 / $3.75
- Context1.05M
Too close to call
It is close. Our weighted score puts them within 2 points (Gemini 3.8 Flash 75/100, Muse Spark 1.3 73/100, Muse Spark 1.1 70/100), so choose by what matters most for your work: Gemini 3.8 Flash for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemini 3.8 FlashCapabilities Index (ECI): Gemini 3.8 Flash 156.9 · Muse Spark 1.3 156.9 · Muse Spark 1.1 154.3
- Lowest priceGemini 3.8 FlashGemini 3.8 Flash $1.50 · Muse Spark 1.3 $2.00 · Muse Spark 1.1 $2.00 per 1M tokens (3:1 blend)
- Longest contextAbout the sameMuse Spark 1.3 1,048,576 · Muse Spark 1.1 1,048,576 · Gemini 3.8 Flash 1,048,576 tokens
- Widest inputsMuse Spark 1.3 and Gemini 3.8 FlashMuse Spark 1.3: Text, Images, PDFs, Audio, Video · Muse Spark 1.1: Text, Images, PDFs, Video · Gemini 3.8 Flash: Text, Images, PDFs, Audio, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Muse Spark 1.3 | Muse Spark 1.1 | Gemini 3.8 Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 87 | 84 | 87 |
| Price | 25% | 36 | 36 | 42 |
| Inputs & features | 15% | 100 | 90 | 100 |
| Context window | 10% | 61 | 61 | 61 |
| Overall | 100% | 73/100 | 70/100 | 75/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Muse Spark 1.3Meta | Muse Spark 1.1Meta | Gemini 3.8 FlashGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.9 | 154.3 | 156.9 (best) |
| ECI rank | #17 of 148 | #35 of 148 | #15 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | — | 95.4% |
| FrontierMath Tiers 1–3Research-level mathematics | 74.4% (best) | — | 68.4% |
| OTIS Mock AIME 2024–2025Competition mathematics | 99.2% (best) | — | 98.9% |
| SimpleQA VerifiedShort factual questions | — | 57.8% | 69.7% (best) |
| Price per million tokens | |||
| Input | $1.25 | $1.25 | $0.75 (best) |
| Output | $4.25 | $4.25 | $3.75 (best) |
| Cached input | $0.15 | $0.15 | $0.075 (best) |
| Blended (3:1) | $2.00 | $2.00 | $1.50 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Meta API | Official Meta API | Official Google API |
| Limits | |||
| Context window | 1,048,576 tokens | 1,048,576 tokens | 1,048,576 tokens |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | Yes | Yes |
| Audio | Yes | No | Yes |
| Video | Yes | Yes | Yes |
| Reasoning | Yesminimal · low · medium · high · xhigh · max | Yesminimal · low · medium · high · xhigh | Yeslow · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | muse-spark-1.3 | muse-spark-1.1 | gemini-3.8-flash |
| API providers | 12 | 13 | 21 (best) |
| Released | Sep 2, 2026 | Jul 9, 2026 | Sep 2, 2026 |
| Knowledge cutoff | — | — | — |
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 1.3$21.00
- Muse Spark 1.1$21.00
- Gemini 3.8 Flash$15.00
Which should you choose?
Which is better: Muse Spark 1.3, Muse Spark 1.1 or Gemini 3.8 Flash?
It is close. Our weighted score puts them within 2 points (Gemini 3.8 Flash 75/100, Muse Spark 1.3 73/100, Muse Spark 1.1 70/100), so choose by what matters most for your work: Gemini 3.8 Flash for raw capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Muse Spark 1.3, Muse Spark 1.1 or Gemini 3.8 Flash?
Gemini 3.8 Flash is cheaper at $0.75 input / $3.75 output per million tokens (official Google API price). Muse Spark 1.3 costs $1.25 input / $4.25 output per million tokens (official Meta 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 $1.50 per million tokens for Gemini 3.8 Flash versus $2.00 for Muse Spark 1.3 (1.3× as much) and $2.00 for Muse Spark 1.1 (1.3× as much).
Which scores higher on benchmarks?
Gemini 3.8 Flash scores higher on the Capabilities Index (ECI): Gemini 3.8 Flash 156.9 (#15 of 148), Muse Spark 1.3 156.9 (#17 of 148) and Muse Spark 1.1 154.3 (#35 of 148). The confidence ranges of the top two overlap (154.6–160.4 vs 154.7–159.6), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Muse Spark 1.3, Muse Spark 1.1 and Gemini 3.8 Flash yet, so there is no like-for-like coding score. On overall capability, Gemini 3.8 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 1.3, Muse Spark 1.1 and Gemini 3.8 Flash share the same 1,048,576-token context window. Maximum output per response: Muse Spark 1.3 up to 131,072, Muse Spark 1.1 up to 131,072, Gemini 3.8 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Muse Spark 1.3 accepts text, images, PDFs, audio and video; Muse Spark 1.1 accepts text, images, PDFs and video; Gemini 3.8 Flash accepts text, images, PDFs, audio and video. Muse Spark 1.3 handles the widest range of inputs.
Are any of these open source?
No. Muse Spark 1.3, Muse Spark 1.1 and Gemini 3.8 Flash are proprietary and only available through APIs and apps.
Which is newer?
Muse Spark 1.3 is the newest, released Sep 2, 2026. Gemini 3.8 Flash came out Sep 2, 2026; Muse Spark 1.1 came out Jul 9, 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.
