GLM-5-Turbo vs GLM-5V-Turbo
GLM-5V-Turbo comes out ahead, 49 to 38 on our weighted score.
Z.ai (Zhipu)GLM-5-Turbo
38/100- ECI—
- Price$1.20 / $4.00
- Context200K
- Our pickZ.ai (Zhipu)
GLM-5V-Turbo
49/100- ECI—
- Price$1.20 / $4.00
- Context200K
Add a model
Make it a three-way comparison.
GLM-5V-Turbo is our pick
GLM-5V-Turbo is the better all-round choice, scoring 49/100 against GLM-5-Turbo (38). It leads on 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 priceSame priceGLM-5-Turbo $1.90 · GLM-5V-Turbo $1.90 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGLM-5-Turbo 200,000 · GLM-5V-Turbo 200,000 tokens
- Widest inputsGLM-5V-TurboGLM-5-Turbo: Text · GLM-5V-Turbo: Text, Images, PDFs, Video
- Self-hostingNo open weightsBoth are available only through APIs
| Measure | Weight | GLM-5-Turbo | GLM-5V-Turbo |
|---|---|---|---|
| Price | 50% | 37 | 37 |
| Inputs & features | 30% | 45 | 80 |
| Context window | 20% | 32 | 32 |
| Overall | 100% | 38/100 | 49/100 |
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-5-TurboZ.ai (Zhipu) | GLM-5V-TurboZ.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $1.20 | $1.20 |
| Output | $4.00 | $4.00 |
| Cached input | $0.24 | $0.24 |
| Blended (3:1) | $1.90 | $1.90 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Z.AI API |
| Limits | ||
| Context window | 200,000 tokens | 200,000 tokens |
| Max output | 131,072 tokens | 131,072 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | Yes |
| PDFs | No | Yes |
| Audio | No | No |
| Video | No | Yes |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Proprietary | Proprietary |
| API model ID | glm-5-turbo | glm-5v-turbo |
| API providers | 17 (best) | 14 |
| Released | Mar 16, 2026 | Apr 1, 2026 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-5-Turbo$20.00
- GLM-5V-Turbo$20.00
Which should you choose?
Which is better: GLM-5-Turbo or GLM-5V-Turbo?
GLM-5V-Turbo is the better all-round choice, scoring 49/100 against GLM-5-Turbo (38). It leads on 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, GLM-5-Turbo or GLM-5V-Turbo?
GLM-5-Turbo and GLM-5V-Turbo cost the same: $1.20 input / $4.00 output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-5-Turbo 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 GLM-5-Turbo and GLM-5V-Turbo yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Both support tool calling for agent workflows.
Which has the bigger context window?
GLM-5-Turbo and GLM-5V-Turbo share the same 200,000-token context window. Maximum output per response: GLM-5-Turbo up to 131,072, GLM-5V-Turbo up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-5-Turbo accepts text; GLM-5V-Turbo accepts text, images, PDFs and video. GLM-5V-Turbo handles the widest range of inputs.
Are any of these open source?
No. GLM-5-Turbo and GLM-5V-Turbo are proprietary and only available through APIs and apps.
Which is newer?
GLM-5V-Turbo is the newest, released Apr 1, 2026. GLM-5-Turbo came out Mar 16, 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.
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