Gemini Robotics-ER 1.6 Preview vs GLM-5V-Turbo vs Qwen3.5 122B-A10B
Qwen3.5 122B-A10B comes out ahead, 58 to 50 and 49 on our weighted score, and it is the cheaper option too.
GoogleGemini Robotics-ER 1.6 Preview
50/100- ECI—
- Price$1.00 / $5.00
- Context131K
Z.ai (Zhipu)GLM-5V-Turbo
49/100- ECI—
- Price$1.20 / $4.00
- Context200K
- Our pick
Alibaba (Qwen)Qwen3.5 122B-A10B
58/100- ECI—
- Price$0.40 / $3.20
- Context262K
Qwen3.5 122B-A10B is our pick
Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against Gemini Robotics-ER 1.6 Preview (50) and GLM-5V-Turbo (49). It leads on price and 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 priceQwen3.5 122B-A10BQwen3.5 122B-A10B $1.10 · GLM-5V-Turbo $1.90 · Gemini Robotics-ER 1.6 Preview $2.00 per 1M tokens (3:1 blend)
- Longest contextQwen3.5 122B-A10BQwen3.5 122B-A10B 262,144 · GLM-5V-Turbo 200,000 · Gemini Robotics-ER 1.6 Preview 131,072 tokens
- Widest inputsSame inputsGemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video · GLM-5V-Turbo: Text, Images, PDFs, Video · Qwen3.5 122B-A10B: Text, Images, Audio, Video
- Self-hostingQwen3.5 122B-A10BPublishes downloadable weights
| Measure | Weight | Gemini Robotics-ER 1.6 Preview | GLM-5V-Turbo | Qwen3.5 122B-A10B |
|---|---|---|---|---|
| Price | 50% | 36 | 37 | 48 |
| Inputs & features | 30% | 90 | 80 | 90 |
| Context window | 20% | 24 | 32 | 37 |
| Overall | 100% | 50/100 | 49/100 | 58/100 |
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 | Gemini Robotics-ER 1.6 PreviewGoogle | GLM-5V-TurboZ.ai (Zhipu) | Qwen3.5 122B-A10BAlibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.00 | $1.20 | $0.40 (best) |
| Output | $5.00 | $4.00 | $3.20 (best) |
| Cached input | — | $0.24 | — |
| Blended (3:1) | $2.00 | $1.90 | $1.10 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Z.AI API | Official Alibaba API |
| Limits | |||
| Context window | 131,072 tokens | 200,000 tokens | 262,144 tokens (best) |
| Max output | 65,536 tokens | 131,072 tokens (best) | 65,536 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | Yes | No | Yes |
| Video | Yes | Yes | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Open |
| API model ID | — | glm-5v-turbo | qwen3.5-122b-a10b |
| API providers | 1 | 14 | 19 (best) |
| Released | Apr 14, 2026 | Apr 1, 2026 | Feb 23, 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.
- Gemini Robotics-ER 1.6 Preview$20.00
- GLM-5V-Turbo$20.00
- Qwen3.5 122B-A10B$10.40
Which should you choose?
Which is better: Gemini Robotics-ER 1.6 Preview, GLM-5V-Turbo or Qwen3.5 122B-A10B?
Qwen3.5 122B-A10B is the better all-round choice, scoring 58/100 against Gemini Robotics-ER 1.6 Preview (50) and GLM-5V-Turbo (49). It leads on price and 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, Gemini Robotics-ER 1.6 Preview, GLM-5V-Turbo or Qwen3.5 122B-A10B?
Qwen3.5 122B-A10B is cheaper at $0.40 input / $3.20 output per million tokens (official Alibaba API price). GLM-5V-Turbo costs $1.20 input / $4.00 output per million tokens (official Z.AI 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 $1.10 per million tokens for Qwen3.5 122B-A10B versus $1.90 for GLM-5V-Turbo (1.7× as much) and $2.00 for Gemini Robotics-ER 1.6 Preview (1.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini Robotics-ER 1.6 Preview has not been scored yet, GLM-5V-Turbo has not been scored yet and Qwen3.5 122B-A10B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini Robotics-ER 1.6 Preview, GLM-5V-Turbo and Qwen3.5 122B-A10B 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?
Qwen3.5 122B-A10B has the largest context window at 262,144 tokens, against 200,000 for GLM-5V-Turbo and 131,072 for Gemini Robotics-ER 1.6 Preview. Maximum output per response: Gemini Robotics-ER 1.6 Preview up to 65,536, GLM-5V-Turbo up to 131,072, Qwen3.5 122B-A10B up to 65,536 tokens.
Which can read images, PDFs, audio or video?
Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video; GLM-5V-Turbo accepts text, images, PDFs and video; Qwen3.5 122B-A10B accepts text, images, audio and video. They handle the same number of input types.
Are any of these open source?
Qwen3.5 122B-A10B publishes its weights and can be self-hosted; Gemini Robotics-ER 1.6 Preview and GLM-5V-Turbo is proprietary.
Which is newer?
Gemini Robotics-ER 1.6 Preview is the newest, released Apr 14, 2026. GLM-5V-Turbo came out Apr 1, 2026; Qwen3.5 122B-A10B came out Feb 23, 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.
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