Gemini 3.8 Flash vs Solar Pro 4 vs Muse Spark 1.3
Too close to call on our weighted score (Gemini 3.8 Flash 63, Muse Spark 1.3 60, Solar Pro 4 55). The right pick depends on what you value most.
GoogleGemini 3.8 Flash
63/100- ECI156.9
- Price$0.75 / $3.75
- Context1.05M
Upstage
Solar Pro 4
55/100- ECI—
- Price$0.30 / $1.20
- Context524K
MetaMuse Spark 1.3
60/100- ECI156.9
- Price$1.25 / $4.25
- Context1.05M
Too close to call
It is close. Our weighted score puts them within 3 points (Gemini 3.8 Flash 63/100, Muse Spark 1.3 60/100, Solar Pro 4 55/100), so choose by what matters most for your work: Solar Pro 4 on price. 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 priceSolar Pro 4Solar Pro 4 $0.525 · Gemini 3.8 Flash $1.50 · Muse Spark 1.3 $2.00 per 1M tokens (3:1 blend)
- Longest contextGemini 3.8 Flash and Muse Spark 1.3Gemini 3.8 Flash 1,048,576 · Muse Spark 1.3 1,048,576 · Solar Pro 4 524,288 tokens
- Widest inputsGemini 3.8 Flash and Muse Spark 1.3Gemini 3.8 Flash: Text, Images, PDFs, Audio, Video · Solar Pro 4: Text · Muse Spark 1.3: Text, Images, PDFs, Audio, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Gemini 3.8 Flash | Solar Pro 4 | Muse Spark 1.3 |
|---|---|---|---|---|
| Price | 50% | 42 | 63 | 36 |
| Inputs & features | 30% | 100 | 45 | 100 |
| Context window | 20% | 61 | 49 | 61 |
| Overall | 100% | 63/100 | 55/100 | 60/100 |
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 | Gemini 3.8 FlashGoogle | Solar Pro 4Upstage | Muse Spark 1.3Meta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.9 (best) | — | 156.9 |
| ECI rank | #15 of 148 (best) | — | #17 of 148 |
| GPQA DiamondGraduate-level science questions | 95.4% | — | — |
| FrontierMath Tiers 1–3Research-level mathematics | 68.4% | — | 74.4% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 98.9% | — | 99.2% (best) |
| SimpleQA VerifiedShort factual questions | 69.7% | — | — |
| Price per million tokens | |||
| Input | $0.75 | $0.30 (best) | $1.25 |
| Output | $3.75 | $1.20 (best) | $4.25 |
| Cached input | $0.075 | $0.06 (best) | $0.15 |
| Blended (3:1) | $1.50 | $0.525 (best) | $2.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Official Upstage API | Official Meta API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 524,288 tokens | 1,048,576 tokens (best) |
| Max output | 65,536 tokens | 131,072 tokens (best) | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | Yes |
| Audio | Yes | No | Yes |
| Video | Yes | No | Yes |
| Reasoning | Yeslow · medium · high | Yesminimal · low · medium · high · xhigh · max | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gemini-3.8-flash | solar-pro4 | muse-spark-1.3 |
| API providers | 21 (best) | 3 | 12 |
| Released | Sep 2, 2026 | Aug 6, 2026 | Sep 2, 2026 |
| Knowledge cutoff | — | Feb 2026 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 3.8 Flash$15.00
- Solar Pro 4$5.40
- Muse Spark 1.3$21.00
Which should you choose?
Which is better: Gemini 3.8 Flash, Solar Pro 4 or Muse Spark 1.3?
It is close. Our weighted score puts them within 3 points (Gemini 3.8 Flash 63/100, Muse Spark 1.3 60/100, Solar Pro 4 55/100), so choose by what matters most for your work: Solar Pro 4 on price. 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, Gemini 3.8 Flash, Solar Pro 4 or Muse Spark 1.3?
Solar Pro 4 is cheaper at $0.30 input / $1.20 output per million tokens (official Upstage API price). Gemini 3.8 Flash costs $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). At a typical mix of three input tokens to one output token, that is $0.525 per million tokens for Solar Pro 4 versus $1.50 for Gemini 3.8 Flash (2.9× as much) and $2.00 for Muse Spark 1.3 (3.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 3.8 Flash has an ECI of 156.9, Solar Pro 4 has not been scored yet and Muse Spark 1.3 has an ECI of 156.9.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 3.8 Flash, Solar Pro 4 and Muse Spark 1.3 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?
Gemini 3.8 Flash and Muse Spark 1.3 have the largest context windows (1,048,576 and 1,048,576 tokens), against 524,288 for Solar Pro 4. Maximum output per response: Gemini 3.8 Flash up to 65,536, Solar Pro 4 up to 131,072, Muse Spark 1.3 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Gemini 3.8 Flash accepts text, images, PDFs, audio and video; Solar Pro 4 accepts text; Muse Spark 1.3 accepts text, images, PDFs, audio and video. Gemini 3.8 Flash handles the widest range of inputs.
Are any of these open source?
No. Gemini 3.8 Flash, Solar Pro 4 and Muse Spark 1.3 are proprietary and only available through APIs and apps.
Which is newer?
Gemini 3.8 Flash is the newest, released Sep 2, 2026. Muse Spark 1.3 came out Sep 2, 2026; Solar Pro 4 came out Aug 6, 2026. Knowledge cutoff: Solar Pro 4 Feb 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.
