Gemini Robotics-ER 1.6 Preview vs Laguna XS.2 vs GLM-5V-Turbo
Gemini Robotics-ER 1.6 Preview comes out ahead, 64 to 61 and 36 on our weighted score, though GLM-5V-Turbo is 5% cheaper per token.
- Our pick
GoogleGemini Robotics-ER 1.6 Preview
64/100- ECI—
- Price$1.00 / $5.00
- Context131K
PoolsideLaguna XS.2
36/100- ECI—
- Price—
- Context262K
Z.ai (Zhipu)GLM-5V-Turbo
61/100- ECI—
- Price$1.20 / $4.00
- Context200K
Gemini Robotics-ER 1.6 Preview is our pick
Gemini Robotics-ER 1.6 Preview is the better all-round choice, scoring 64/100 against GLM-5V-Turbo (61) and Laguna XS.2 (36). It leads on inputs & features. Laguna XS.2 wins on context window. The score weighs inputs & features 60%, context window 40%. 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 · Gemini Robotics-ER 1.6 Preview $2.00 per 1M tokens (3:1 blend) · Laguna XS.2 unpriced
- Longest contextLaguna XS.2Laguna XS.2 262,144 · GLM-5V-Turbo 200,000 · Gemini Robotics-ER 1.6 Preview 131,072 tokens
- Widest inputsGemini Robotics-ER 1.6 Preview and GLM-5V-TurboGemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video · Laguna XS.2: Text · GLM-5V-Turbo: Text, Images, PDFs, Video
- Self-hostingLaguna XS.2Publishes downloadable weights
| Measure | Weight | Gemini Robotics-ER 1.6 Preview | Laguna XS.2 | GLM-5V-Turbo |
|---|---|---|---|---|
| Inputs & features | 60% | 90 | 35 | 80 |
| Context window | 40% | 24 | 37 | 32 |
| Overall | 100% | 64/100 | 36/100 | 61/100 |
Left out because at least one model lacks the data: capability and price. 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 | Laguna XS.2Poolside | GLM-5V-TurboZ.ai (Zhipu) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.00 (best) | — | $1.20 |
| Output | $5.00 | — | $4.00 (best) |
| Cached input | — | — | $0.24 |
| Blended (3:1) | $2.00 | — | $1.90 (best) |
| Long-context rate | Same rate | — | Same rate |
| Price source | Median of 1 providers | — | Official Z.AI API |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens (best) | 200,000 tokens |
| Max output | 65,536 tokens | 32,768 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | Yes | No | No |
| Video | Yes | No | Yes |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | — | — | glm-5v-turbo |
| API providers | 1 | 1 | 14 (best) |
| Released | Apr 14, 2026 | Apr 28, 2026 | Apr 1, 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
- Laguna XS.2—
- GLM-5V-Turbo$20.00
Which should you choose?
Which is better: Gemini Robotics-ER 1.6 Preview, Laguna XS.2 or GLM-5V-Turbo?
Gemini Robotics-ER 1.6 Preview is the better all-round choice, scoring 64/100 against GLM-5V-Turbo (61) and Laguna XS.2 (36). It leads on inputs & features. Laguna XS.2 wins on context window. The score weighs inputs & features 60%, context window 40%. 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, Laguna XS.2 or GLM-5V-Turbo?
GLM-5V-Turbo is cheaper at $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 $1.90 per million tokens for GLM-5V-Turbo versus $2.00 for Gemini Robotics-ER 1.6 Preview (1.1× as much). Laguna XS.2 has no published per-token price.
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, Laguna XS.2 has not been scored yet and GLM-5V-Turbo 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, Laguna XS.2 and GLM-5V-Turbo 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?
Laguna XS.2 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, Laguna XS.2 up to 32,768, GLM-5V-Turbo up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Gemini Robotics-ER 1.6 Preview accepts text, images, audio and video; Laguna XS.2 accepts text; GLM-5V-Turbo accepts text, images, PDFs and video. Gemini Robotics-ER 1.6 Preview handles the widest range of inputs.
Are any of these open source?
Laguna XS.2 publishes its weights and can be self-hosted; Gemini Robotics-ER 1.6 Preview and GLM-5V-Turbo is proprietary.
Which is newer?
Laguna XS.2 is the newest, released Apr 28, 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.
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