Gemini 3.8 Flash vs DeepSeek V4.1 Flash vs Muse Spark 1.3
DeepSeek V4.1 Flash comes out ahead, 78 to 75 and 73 on our weighted score, and it is the cheaper option too.
GoogleGemini 3.8 Flash
75/100- ECI156.9
- Price$0.75 / $3.75
- Context1.05M
- Our pick
DeepSeekDeepSeek V4.1 Flash
78/100- ECI155.0
- Price$0.15 / $0.60
- Context1M
MetaMuse Spark 1.3
73/100- ECI156.9
- Price$1.25 / $4.25
- Context1.05M
DeepSeek V4.1 Flash is our pick
DeepSeek V4.1 Flash is the better all-round choice, scoring 78/100 against Gemini 3.8 Flash (75) and Muse Spark 1.3 (73). It leads on price. 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 · DeepSeek V4.1 Flash 155.0
- Lowest priceDeepSeek V4.1 FlashDeepSeek V4.1 Flash $0.263 · 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 · DeepSeek V4.1 Flash 1,000,000 tokens
- Widest inputsGemini 3.8 Flash and Muse Spark 1.3Gemini 3.8 Flash: Text, Images, PDFs, Audio, Video · DeepSeek V4.1 Flash: Text, Images · Muse Spark 1.3: Text, Images, PDFs, Audio, Video
- Self-hostingDeepSeek V4.1 FlashPublishes downloadable weights (MIT)
| Measure | Weight | Gemini 3.8 Flash | DeepSeek V4.1 Flash | Muse Spark 1.3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 87 | 84 | 87 |
| Price | 25% | 42 | 77 | 36 |
| Inputs & features | 15% | 100 | 70 | 100 |
| Context window | 10% | 61 | 60 | 61 |
| Overall | 100% | 75/100 | 78/100 | 73/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 3.8 FlashGoogle | DeepSeek V4.1 FlashDeepSeek | Muse Spark 1.3Meta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 156.9 (best) | 155.0 | 156.9 |
| ECI rank | #15 of 148 (best) | #29 of 148 | #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 | $0.15 (best) | $1.25 |
| Output | $3.75 | $0.60 (best) | $4.25 |
| Cached input | $0.075 | $0.003 (best) | $0.15 |
| Blended (3:1) | $1.50 | $0.263 (best) | $2.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Google API | Official DeepSeek API | Official Meta API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,000,000 tokens | 1,048,576 tokens (best) |
| Max output | 65,536 tokens | 384,000 tokens (best) | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | Yes |
| Audio | Yes | No | Yes |
| Video | Yes | No | Yes |
| Reasoning | Yeslow · medium · high | Yeslow · high · max | Yesminimal · low · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | OpenMIT | Proprietary |
| API model ID | gemini-3.8-flash | deepseek-flash | muse-spark-1.3 |
| API providers | 21 | 50 (best) | 12 |
| Released | Sep 2, 2026 | Sep 10, 2026 | Sep 2, 2026 |
| Knowledge cutoff | — | May 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 3.8 Flash$15.00
- DeepSeek V4.1 Flash$2.70
- Muse Spark 1.3$21.00
Which should you choose?
Which is better: Gemini 3.8 Flash, DeepSeek V4.1 Flash or Muse Spark 1.3?
DeepSeek V4.1 Flash is the better all-round choice, scoring 78/100 against Gemini 3.8 Flash (75) and Muse Spark 1.3 (73). It leads on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 3.8 Flash, DeepSeek V4.1 Flash or Muse Spark 1.3?
DeepSeek V4.1 Flash is cheaper at $0.15 input / $0.60 output per million tokens (official DeepSeek 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 $0.263 per million tokens for DeepSeek V4.1 Flash versus $1.50 for Gemini 3.8 Flash (5.7× as much) and $2.00 for Muse Spark 1.3 (7.6× 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 DeepSeek V4.1 Flash 155.0 (#29 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 Gemini 3.8 Flash, DeepSeek V4.1 Flash and Muse Spark 1.3 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?
Gemini 3.8 Flash and Muse Spark 1.3 have the largest context windows (1,048,576 and 1,048,576 tokens), against 1,000,000 for DeepSeek V4.1 Flash. Maximum output per response: Gemini 3.8 Flash up to 65,536, DeepSeek V4.1 Flash up to 384,000, 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; DeepSeek V4.1 Flash accepts text and images; 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?
DeepSeek V4.1 Flash publishes its weights (MIT) and can be self-hosted; Gemini 3.8 Flash and Muse Spark 1.3 is proprietary.
Which is newer?
DeepSeek V4.1 Flash is the newest, released Sep 10, 2026. Gemini 3.8 Flash came out Sep 2, 2026; Muse Spark 1.3 came out Sep 2, 2026. Knowledge cutoff: DeepSeek V4.1 Flash May 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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