DeepSeek V4.1 Flash vs Muse Spark 1.3 vs GLM-5.3-Flash
Too close to call on our weighted score (GLM-5.3-Flash 80, DeepSeek V4.1 Flash 78, Muse Spark 1.3 73). The right pick depends on what you value most.
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
Z.ai (Zhipu)GLM-5.3-Flash
80/100- ECI151.9
- Price$0.15 / $0.50
- Context1M
Too close to call
It is close. Our weighted score puts them within 2 points (GLM-5.3-Flash 80/100, DeepSeek V4.1 Flash 78/100, Muse Spark 1.3 73/100), so choose by what matters most for your work: Muse Spark 1.3 for raw capability and GLM-5.3-Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityMuse Spark 1.3Capabilities Index (ECI): Muse Spark 1.3 156.9 · DeepSeek V4.1 Flash 155.0 · GLM-5.3-Flash 151.9
- Lowest priceGLM-5.3-FlashGLM-5.3-Flash $0.237 · DeepSeek V4.1 Flash $0.263 · Muse Spark 1.3 $2.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.3Muse Spark 1.3 1,048,576 · DeepSeek V4.1 Flash 1,000,000 · GLM-5.3-Flash 1,000,000 tokens
- Widest inputsMuse Spark 1.3DeepSeek V4.1 Flash: Text, Images · Muse Spark 1.3: Text, Images, PDFs, Audio, Video · GLM-5.3-Flash: Text, Images, PDFs, Video
- Self-hostingDeepSeek V4.1 Flash and GLM-5.3-FlashPublishes downloadable weights (MIT)
| Measure | Weight | DeepSeek V4.1 Flash | Muse Spark 1.3 | GLM-5.3-Flash |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 84 | 87 | 81 |
| Price | 25% | 77 | 36 | 79 |
| Inputs & features | 15% | 70 | 100 | 90 |
| Context window | 10% | 60 | 61 | 60 |
| Overall | 100% | 78/100 | 73/100 | 80/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | DeepSeek V4.1 FlashDeepSeek | Muse Spark 1.3Meta | GLM-5.3-FlashZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 155.0 | 156.9 (best) | 151.9 |
| ECI rank | #29 of 148 | #17 of 148 (best) | #42 of 148 |
| GPQA DiamondGraduate-level science questions | — | — | 90.2% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 74.4% (best) | 55.8% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 99.2% (best) | 93.9% |
| Price per million tokens | |||
| Input | $0.15 (best) | $1.25 | $0.15 (best) |
| Output | $0.60 | $4.25 | $0.50 (best) |
| Cached input | $0.003 (best) | $0.15 | $0.03 |
| Blended (3:1) | $0.263 | $2.00 | $0.237 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official DeepSeek API | Official Meta API | Official Z.AI API |
| Limits | |||
| Context window | 1,000,000 tokens | 1,048,576 tokens (best) | 1,000,000 tokens |
| Max output | 384,000 tokens (best) | 131,072 tokens | 131,072 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | Yes | No |
| Video | No | Yes | Yes |
| Reasoning | Yeslow · high · max | Yesminimal · low · medium · high · xhigh · max | Yeslow · high · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | OpenMIT | Proprietary | Open |
| API model ID | deepseek-flash | muse-spark-1.3 | glm-5.3-flash |
| API providers | 50 | 12 | 65 (best) |
| Released | Sep 10, 2026 | Sep 2, 2026 | Aug 26, 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.
- DeepSeek V4.1 Flash$2.70
- Muse Spark 1.3$21.00
- GLM-5.3-Flash$2.50
Which should you choose?
Which is better: DeepSeek V4.1 Flash, Muse Spark 1.3 or GLM-5.3-Flash?
It is close. Our weighted score puts them within 2 points (GLM-5.3-Flash 80/100, DeepSeek V4.1 Flash 78/100, Muse Spark 1.3 73/100), so choose by what matters most for your work: Muse Spark 1.3 for raw capability and GLM-5.3-Flash on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek V4.1 Flash, Muse Spark 1.3 or GLM-5.3-Flash?
GLM-5.3-Flash is cheaper at $0.15 input / $0.50 output per million tokens (official Z.AI API price). DeepSeek V4.1 Flash costs $0.15 input / $0.60 output per million tokens (official DeepSeek 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 $0.237 per million tokens for GLM-5.3-Flash versus $0.263 for DeepSeek V4.1 Flash (1.1× as much) and $2.00 for Muse Spark 1.3 (8.4× as much).
Which scores higher on benchmarks?
Muse Spark 1.3 scores higher on the Capabilities Index (ECI): Muse Spark 1.3 156.9 (#17 of 148), DeepSeek V4.1 Flash 155.0 (#29 of 148) and GLM-5.3-Flash 151.9 (#42 of 148). The confidence ranges of the top two overlap (154.7–159.6 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, Muse Spark 1.3 and GLM-5.3-Flash yet, so there is no like-for-like coding score. On overall capability, Muse Spark 1.3 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 has the largest context window at 1,048,576 tokens, against 1,000,000 for DeepSeek V4.1 Flash and 1,000,000 for GLM-5.3-Flash. Maximum output per response: DeepSeek V4.1 Flash up to 384,000, Muse Spark 1.3 up to 131,072, GLM-5.3-Flash up to 131,072 tokens.
Which can read images, PDFs, audio or video?
DeepSeek V4.1 Flash accepts text and images; Muse Spark 1.3 accepts text, images, PDFs, audio and video; GLM-5.3-Flash accepts text, images, PDFs and video. Muse Spark 1.3 handles the widest range of inputs.
Are any of these open source?
DeepSeek V4.1 Flash and GLM-5.3-Flash publishes its weights (MIT) and can be self-hosted; Muse Spark 1.3 is proprietary.
Which is newer?
DeepSeek V4.1 Flash is the newest, released Sep 10, 2026. Muse Spark 1.3 came out Sep 2, 2026; GLM-5.3-Flash came out Aug 26, 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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