ZMIME
Comparison · 3 models · Updated Oct 4, 2026

Gemini Robotics-ER 1.6 Preview vs QwQ 32B vs GLM-5V-Turbo

Too close to call on our weighted score (Gemini Robotics-ER 1.6 Preview 50, GLM-5V-Turbo 49, QwQ 32B 43). The right pick depends on what you value most.

  1. Google

    Gemini Robotics-ER 1.6 Preview

    Released Apr 14, 2026

    50/100
    • ECI—
    • Price$1.00 / $5.00
    • Context131K
  2. Alibaba (Qwen)

    QwQ 32B

    Released Mar 5, 2025

    43/100
    • ECI137.6
    • Price$0.66 / $1.00
    • Context131K
  3. Z.ai (Zhipu)

    GLM-5V-Turbo

    Released Apr 1, 2026

    49/100
    • ECI—
    • Price$1.20 / $4.00
    • Context200K
01 — Verdict

Too close to call

It is close. Our weighted score puts them within 1 points (Gemini Robotics-ER 1.6 Preview 50/100, GLM-5V-Turbo 49/100, QwQ 32B 43/100), so choose by what matters most for your work: QwQ 32B on price and GLM-5V-Turbo for long inputs. 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 priceQwQ 32BQwQ 32B $0.745 · GLM-5V-Turbo $1.90 · Gemini Robotics-ER 1.6 Preview $2.00 per 1M tokens (3:1 blend)
  • Longest contextGLM-5V-TurboGLM-5V-Turbo 200,000 · Gemini Robotics-ER 1.6 Preview 131,072 · QwQ 32B 131,072 tokens
  • Widest inputsGemini Robotics-ER 1.6 Preview and GLM-5V-TurboGemini Robotics-ER 1.6 Preview: Text, Images, Audio, Video · QwQ 32B: Text · GLM-5V-Turbo: Text, Images, PDFs, Video
  • Self-hostingQwQ 32BPublishes downloadable weights
How the score is built
MeasureWeightGemini Robotics-ER 1.6 PreviewQwQ 32BGLM-5V-Turbo
Price50%365637
Inputs & features30%903580
Context window20%242432
Overall100%50/10043/10049/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Gemini Robotics-ER 1.6 Preview vs QwQ 32B vs GLM-5V-Turbo specifications side by side
SpecificationGemini Robotics-ER 1.6 PreviewGoogleQwQ 32BAlibaba (Qwen)GLM-5V-TurboZ.ai (Zhipu)
Capability
Capabilities Index (ECI)—137.6—
ECI rank—#109 of 148—
GPQA DiamondGraduate-level science questions—65.3%—
OTIS Mock AIME 2024–2025Competition mathematics—59.2%—
Price per million tokens
Input$1.00$0.66 (best)$1.20
Output$5.00$1.00 (best)$4.00
Cached input——$0.24
Blended (3:1)$2.00$0.745 (best)$1.90
Long-context rateSame rateSame rateSame rate
Price sourceMedian of 1 providersMedian of 1 providersOfficial Z.AI API
Limits
Context window131,072 tokens131,072 tokens200,000 tokens (best)
Max output65,536 tokens8,192 tokens131,072 tokens (best)
Inputs and features
TextYesYesYes
ImagesYesNoYes
PDFsNoNoYes
AudioYesNoNo
VideoYesNoYes
ReasoningYesYesYes
Tool callingYesYesYes
Structured outputYesNoNo
Availability
WeightsProprietaryOpenProprietary
API model ID——glm-5v-turbo
API providers1114 (best)
ReleasedApr 14, 2026Mar 5, 2025Apr 1, 2026
Knowledge cutoffJan 2025Apr 2024—
03 — Cost

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
  • QwQ 32B$8.60
  • GLM-5V-Turbo$20.00
04 — Questions

Which should you choose?

Which is better: Gemini Robotics-ER 1.6 Preview, QwQ 32B or GLM-5V-Turbo?

It is close. Our weighted score puts them within 1 points (Gemini Robotics-ER 1.6 Preview 50/100, GLM-5V-Turbo 49/100, QwQ 32B 43/100), so choose by what matters most for your work: QwQ 32B on price and GLM-5V-Turbo for long inputs. 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, QwQ 32B or GLM-5V-Turbo?

QwQ 32B is cheaper at $0.66 input / $1.00 output per million tokens (median across 1 API provider). 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 $0.745 per million tokens for QwQ 32B versus $1.90 for GLM-5V-Turbo (2.6× as much) and $2.00 for Gemini Robotics-ER 1.6 Preview (2.7× 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, QwQ 32B has an ECI of 137.6 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, QwQ 32B 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?

GLM-5V-Turbo has the largest context window at 200,000 tokens, against 131,072 for Gemini Robotics-ER 1.6 Preview and 131,072 for QwQ 32B. Maximum output per response: Gemini Robotics-ER 1.6 Preview up to 65,536, QwQ 32B up to 8,192, 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; QwQ 32B 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?

QwQ 32B 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; QwQ 32B came out Mar 5, 2025. Knowledge cutoff: Gemini Robotics-ER 1.6 Preview Jan 2025, QwQ 32B Apr 2024.

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.