GLM-5V-Turbo vs Muse Spark 1.1 vs Gemini Robotics-ER 1.6 Preview
Muse Spark 1.1 comes out ahead, 57 to 50 and 49 on our weighted score, though GLM-5V-Turbo is 5% cheaper per token.
Z.ai (Zhipu)GLM-5V-Turbo
49/100- ECI—
- Price$1.20 / $4.00
- Context200K
- Our pick
MetaMuse Spark 1.1
57/100- ECI154.3
- Price$1.25 / $4.25
- Context1.05M
GoogleGemini Robotics-ER 1.6 Preview
50/100- ECI—
- Price$1.00 / $5.00
- Context131K
Muse Spark 1.1 is our pick
Muse Spark 1.1 is the better all-round choice, scoring 57/100 against Gemini Robotics-ER 1.6 Preview (50) and GLM-5V-Turbo (49). It leads on context window. 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 priceGLM-5V-TurboGLM-5V-Turbo $1.90 · Muse Spark 1.1 $2.00 · Gemini Robotics-ER 1.6 Preview $2.00 per 1M tokens (3:1 blend)
- Longest contextMuse Spark 1.1Muse Spark 1.1 1,048,576 · GLM-5V-Turbo 200,000 · Gemini Robotics-ER 1.6 Preview 131,072 tokens
- Widest inputsSame inputsGLM-5V-Turbo: Text, Images, PDFs, Video · Muse Spark 1.1: Text, Images, PDFs, Video · Gemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | GLM-5V-Turbo | Muse Spark 1.1 | Gemini Robotics-ER 1.6 Preview |
|---|---|---|---|---|
| Price | 50% | 37 | 36 | 36 |
| Inputs & features | 30% | 80 | 90 | 90 |
| Context window | 20% | 32 | 61 | 24 |
| Overall | 100% | 49/100 | 57/100 | 50/100 |
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 | GLM-5V-TurboZ.ai (Zhipu) | Muse Spark 1.1Meta | Gemini Robotics-ER 1.6 PreviewGoogle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 154.3 | — |
| ECI rank | — | #35 of 148 | — |
| SimpleQA VerifiedShort factual questions | — | 57.8% | — |
| Price per million tokens | |||
| Input | $1.20 | $1.25 | $1.00 (best) |
| Output | $4.00 (best) | $4.25 | $5.00 |
| Cached input | $0.24 | $0.15 (best) | — |
| Blended (3:1) | $1.90 (best) | $2.00 | $2.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Meta API | Median of 1 providers |
| Limits | |||
| Context window | 200,000 tokens | 1,048,576 tokens (best) | 131,072 tokens |
| 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 | No |
| Audio | No | No | Yes |
| Video | Yes | Yes | Yes |
| Reasoning | Yes | Yesminimal · low · medium · high · xhigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | glm-5v-turbo | muse-spark-1.1 | — |
| API providers | 14 (best) | 13 | 1 |
| Released | Apr 1, 2026 | Jul 9, 2026 | Apr 14, 2026 |
| Knowledge cutoff | — | — | Jan 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5V-Turbo$20.00
- Muse Spark 1.1$21.00
- Gemini Robotics-ER 1.6 Preview$20.00
Which should you choose?
Which is better: GLM-5V-Turbo, Muse Spark 1.1 or Gemini Robotics-ER 1.6 Preview?
Muse Spark 1.1 is the better all-round choice, scoring 57/100 against Gemini Robotics-ER 1.6 Preview (50) and GLM-5V-Turbo (49). It leads on context window. 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, GLM-5V-Turbo, Muse Spark 1.1 or Gemini Robotics-ER 1.6 Preview?
GLM-5V-Turbo is cheaper at $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); Gemini Robotics-ER 1.6 Preview costs $1.00 input / $5.00 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $1.90 per million tokens for GLM-5V-Turbo versus $2.00 for Muse Spark 1.1 (1.1× as much) and $2.00 for Gemini Robotics-ER 1.6 Preview (1.1× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-5V-Turbo has not been scored yet, Muse Spark 1.1 has an ECI of 154.3 and Gemini Robotics-ER 1.6 Preview has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5V-Turbo, Muse Spark 1.1 and Gemini Robotics-ER 1.6 Preview 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 has the largest context window at 1,048,576 tokens, against 200,000 for GLM-5V-Turbo and 131,072 for Gemini Robotics-ER 1.6 Preview. Maximum output per response: GLM-5V-Turbo up to 131,072, Muse Spark 1.1 up to 131,072, Gemini Robotics-ER 1.6 Preview up to 65,536 tokens.
Which can read images, PDFs, audio or video?
GLM-5V-Turbo accepts text, images, PDFs and video; Muse Spark 1.1 accepts text, images, PDFs and video; Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video. They handle the same number of input types.
Are any of these open source?
No. GLM-5V-Turbo, Muse Spark 1.1 and Gemini Robotics-ER 1.6 Preview are proprietary and only available through APIs and apps.
Which is newer?
Muse Spark 1.1 is the newest, released Jul 9, 2026. Gemini Robotics-ER 1.6 Preview came out Apr 14, 2026; GLM-5V-Turbo came out Apr 1, 2026. Knowledge cutoff: Gemini Robotics-ER 1.6 Preview Jan 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.
