Muse Spark 1.1 vs GLM-5V-Turbo vs Gemini 3.6 Flash
Gemini 3.6 Flash comes out ahead, 63 to 57 and 49 on our weighted score, and it is the cheaper option too.
MetaMuse Spark 1.1
57/100- ECI154.3
- Price$1.25 / $4.25
- Context1.05M
Z.ai (Zhipu)GLM-5V-Turbo
49/100- ECI—
- Price$1.20 / $4.00
- Context200K
- Our pick
GoogleGemini 3.6 Flash
63/100- ECI154.3
- Price$0.75 / $3.75
- Context1.05M
Gemini 3.6 Flash is our pick
Gemini 3.6 Flash is the better all-round choice, scoring 63/100 against Muse Spark 1.1 (57) and GLM-5V-Turbo (49). It leads on price and inputs & features. 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 priceGemini 3.6 FlashGemini 3.6 Flash $1.50 · GLM-5V-Turbo $1.90 · Muse Spark 1.1 $2.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.1 and Gemini 3.6 FlashMuse Spark 1.1 1,048,576 · Gemini 3.6 Flash 1,048,576 · GLM-5V-Turbo 200,000 tokens
- Widest inputsGemini 3.6 FlashMuse Spark 1.1: Text, Images, PDFs, Video · GLM-5V-Turbo: Text, Images, PDFs, Video · Gemini 3.6 Flash: Text, Images, PDFs, Audio, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Muse Spark 1.1 | GLM-5V-Turbo | Gemini 3.6 Flash |
|---|---|---|---|---|
| Price | 50% | 36 | 37 | 42 |
| Inputs & features | 30% | 90 | 80 | 100 |
| Context window | 20% | 61 | 32 | 61 |
| Overall | 100% | 57/100 | 49/100 | 63/100 |
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 | Muse Spark 1.1Meta | GLM-5V-TurboZ.ai (Zhipu) | Gemini 3.6 FlashGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 154.3 | — | 154.3 (best) |
| ECI rank | #35 of 148 | — | #34 of 148 (best) |
| GPQA DiamondGraduate-level science questions | — | — | 94.1% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 59.0% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 94.2% |
| SimpleQA VerifiedShort factual questions | 57.8% | — | 66.2% (best) |
| Price per million tokens | |||
| Input | $1.25 | $1.20 | $0.75 (best) |
| Output | $4.25 | $4.00 | $3.75 (best) |
| Cached input | $0.15 | $0.24 | $0.075 (best) |
| Blended (3:1) | $2.00 | $1.90 | $1.50 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Meta API | Official Z.AI API | Official Google API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 200,000 tokens | 1,048,576 tokens (best) |
| 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 | No | No | Yes |
| Video | Yes | Yes | Yes |
| Reasoning | Yesminimal · low · medium · high · xhigh | Yes | Yesminimal · low · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | muse-spark-1.1 | glm-5v-turbo | gemini-3.6-flash |
| API providers | 13 | 14 | 25 (best) |
| Released | Jul 9, 2026 | Apr 1, 2026 | Jul 21, 2026 |
| Knowledge cutoff | — | — | Mar 2026 |
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 1.1$21.00
- GLM-5V-Turbo$20.00
- Gemini 3.6 Flash$15.00
Which should you choose?
Which is better: Muse Spark 1.1, GLM-5V-Turbo or Gemini 3.6 Flash?
Gemini 3.6 Flash is the better all-round choice, scoring 63/100 against Muse Spark 1.1 (57) and GLM-5V-Turbo (49). It leads on price and inputs & features. 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, Muse Spark 1.1, GLM-5V-Turbo or Gemini 3.6 Flash?
Gemini 3.6 Flash is cheaper at $0.75 input / $3.75 output per million tokens (official Google API price). GLM-5V-Turbo costs $1.20 input / $4.00 output per million tokens (official Z.AI 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 3.6 Flash versus $1.90 for GLM-5V-Turbo (1.3× as much) and $2.00 for Muse Spark 1.1 (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Muse Spark 1.1 has an ECI of 154.3, GLM-5V-Turbo has not been scored yet and Gemini 3.6 Flash has an ECI of 154.3.
Which is better for coding?
There are no published SWE-bench Verified results for Muse Spark 1.1, GLM-5V-Turbo and Gemini 3.6 Flash 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?
Muse Spark 1.1 and Gemini 3.6 Flash have the largest context windows (1,048,576 and 1,048,576 tokens), against 200,000 for GLM-5V-Turbo. Maximum output per response: Muse Spark 1.1 up to 131,072, GLM-5V-Turbo up to 131,072, Gemini 3.6 Flash up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Muse Spark 1.1 accepts text, images, PDFs and video; GLM-5V-Turbo accepts text, images, PDFs and video; Gemini 3.6 Flash accepts text, images, PDFs, audio and video. Gemini 3.6 Flash handles the widest range of inputs.
Are any of these open source?
No. Muse Spark 1.1, GLM-5V-Turbo and Gemini 3.6 Flash are proprietary and only available through APIs and apps.
Which is newer?
Gemini 3.6 Flash is the newest, released Jul 21, 2026. Muse Spark 1.1 came out Jul 9, 2026; GLM-5V-Turbo came out Apr 1, 2026. Knowledge cutoff: Gemini 3.6 Flash Mar 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.
