DeepSeek V4.1 Flash vs GPT-5.6 Luna vs Muse Spark 1.1
Too close to call on our weighted score (DeepSeek V4.1 Flash 78, GPT-5.6 Luna 78, Muse Spark 1.1 70). The right pick depends on what you value most.
DeepSeekDeepSeek V4.1 Flash
78/100- ECI155.0
- Price$0.15 / $0.60
- Context1M
OpenAIGPT-5.6 Luna
78/100- ECI156.5
- Price$0.20 / $1.20
- Context1.05M
MetaMuse Spark 1.1
70/100- ECI154.3
- Price$1.25 / $4.25
- Context1.05M
Too close to call
It is close. Our weighted score puts them within a point (DeepSeek V4.1 Flash 78/100, GPT-5.6 Luna 78/100, Muse Spark 1.1 70/100), so choose by what matters most for your work: GPT-5.6 Luna for raw capability and DeepSeek V4.1 Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGPT-5.6 LunaCapabilities Index (ECI): GPT-5.6 Luna 156.5 · DeepSeek V4.1 Flash 155.0 · Muse Spark 1.1 154.3
- Lowest priceDeepSeek V4.1 FlashDeepSeek V4.1 Flash $0.263 · GPT-5.6 Luna $0.45 · Muse Spark 1.1 $2.00 per 1M tokens (3:1 blend)
- Longest contextGPT-5.6 Luna and Muse Spark 1.1GPT-5.6 Luna 1,050,000 · Muse Spark 1.1 1,048,576 · DeepSeek V4.1 Flash 1,000,000 tokens
- Widest inputsMuse Spark 1.1DeepSeek V4.1 Flash: Text, Images · GPT-5.6 Luna: Text, Images, PDFs · Muse Spark 1.1: Text, Images, PDFs, Video
- Self-hostingDeepSeek V4.1 FlashPublishes downloadable weights (MIT)
| Measure | Weight | DeepSeek V4.1 Flash | GPT-5.6 Luna | Muse Spark 1.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 86 | 84 |
| Price | 25% | 77 | 66 | 36 |
| Inputs & features | 15% | 70 | 80 | 90 |
| Context window | 10% | 60 | 61 | 61 |
| Overall | 100% | 78/100 | 78/100 | 70/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek V4.1 FlashDeepSeek | GPT-5.6 LunaOpenAI | Muse Spark 1.1Meta |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 155.0 | 156.5 (best) | 154.3 |
| ECI rank | #29 of 148 | #21 of 148 (best) | #35 of 148 |
| GPQA DiamondGraduate-level science questions | — | 91.6% | — |
| FrontierMath Tiers 1–3Research-level mathematics | — | 82.1% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 98.3% | — |
| SimpleQA VerifiedShort factual questions | — | 41.0% | 57.8% (best) |
| Price per million tokens | |||
| Input | $0.15 (best) | $0.20 | $1.25 |
| Output | $0.60 (best) | $1.20 | $4.25 |
| Cached input | $0.003 (best) | $0.02 | $0.15 |
| Blended (3:1) | $0.263 (best) | $0.45 | $2.00 |
| Long-context rate | Same rate | Over 272K: $0.40 / $1.80 | Same rate |
| Price source | Official DeepSeek API | Official OpenAI API | Official Meta API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,050,000 tokens (best) | 1,048,576 tokens |
| Max output | 384,000 tokens (best) | 128,000 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | No | No |
| Video | No | No | Yes |
| Reasoning | Yeslow · high · max | Yeslow · medium · high · xhigh · max | Yesminimal · low · medium · high · xhigh |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | OpenMIT | Proprietary | Proprietary |
| API model ID | deepseek-flash | gpt-5.6-luna | muse-spark-1.1 |
| API providers | 50 (best) | 38 | 13 |
| Released | Sep 10, 2026 | Jul 9, 2026 | Jul 9, 2026 |
| Knowledge cutoff | May 2025 | Feb 16, 2026 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- DeepSeek V4.1 Flash$2.70
- GPT-5.6 Luna$4.40
- Muse Spark 1.1$21.00
Which should you choose?
Which is better: DeepSeek V4.1 Flash, GPT-5.6 Luna or Muse Spark 1.1?
It is close. Our weighted score puts them within a point (DeepSeek V4.1 Flash 78/100, GPT-5.6 Luna 78/100, Muse Spark 1.1 70/100), so choose by what matters most for your work: GPT-5.6 Luna for raw capability and DeepSeek V4.1 Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek V4.1 Flash, GPT-5.6 Luna or Muse Spark 1.1?
DeepSeek V4.1 Flash is cheaper at $0.15 input / $0.60 output per million tokens (official DeepSeek API price). GPT-5.6 Luna costs $0.20 input / $1.20 output per million tokens (official OpenAI 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 $0.263 per million tokens for DeepSeek V4.1 Flash versus $0.45 for GPT-5.6 Luna (1.7× as much) and $2.00 for Muse Spark 1.1 (7.6× as much).
Which scores higher on benchmarks?
GPT-5.6 Luna scores higher on the Capabilities Index (ECI): GPT-5.6 Luna 156.5 (#21 of 148), DeepSeek V4.1 Flash 155.0 (#29 of 148) and Muse Spark 1.1 154.3 (#35 of 148). The confidence ranges of the top two overlap (154.1–158.6 vs 148.8–157.6), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for DeepSeek V4.1 Flash, GPT-5.6 Luna and Muse Spark 1.1 yet, so there is no like-for-like coding score. On overall capability, GPT-5.6 Luna 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?
GPT-5.6 Luna and Muse Spark 1.1 have the largest context windows (1,050,000 and 1,048,576 tokens), against 1,000,000 for DeepSeek V4.1 Flash. Maximum output per response: DeepSeek V4.1 Flash up to 384,000, GPT-5.6 Luna up to 128,000, Muse Spark 1.1 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4.1 Flash accepts text and images; GPT-5.6 Luna accepts text, images and PDFs; Muse Spark 1.1 accepts text, images, PDFs and video. Muse Spark 1.1 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; GPT-5.6 Luna and Muse Spark 1.1 is proprietary.
Which is newer?
DeepSeek V4.1 Flash is the newest, released Sep 10, 2026. GPT-5.6 Luna came out Jul 9, 2026; Muse Spark 1.1 came out Jul 9, 2026. Knowledge cutoff: DeepSeek V4.1 Flash May 2025, GPT-5.6 Luna Feb 16, 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.
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