GLM-5V-Turbo vs Trinity Large Thinking
Trinity Large Thinking comes out ahead, 55 to 49 on our weighted score, and it is the cheaper option too.
Z.ai (Zhipu)GLM-5V-Turbo
49/100- ECI—
- Price$1.20 / $4.00
- Context200K
- Our pick
Arcee AITrinity Large Thinking
55/100- ECI—
- Price$0.25 / $0.80
- Context524K
Add a model
Make it a three-way comparison.
Trinity Large Thinking is our pick
Trinity Large Thinking is the better all-round choice, scoring 55/100 against GLM-5V-Turbo (49). It leads on price and context window. GLM-5V-Turbo wins 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 priceTrinity Large ThinkingTrinity Large Thinking $0.388 · GLM-5V-Turbo $1.90 per 1M tokens (3:1 blend)
- Longest contextTrinity Large ThinkingTrinity Large Thinking 524,288 · GLM-5V-Turbo 200,000 tokens
- Widest inputsGLM-5V-TurboGLM-5V-Turbo: Text, Images, PDFs, Video · Trinity Large Thinking: Text
- Self-hostingTrinity Large ThinkingPublishes downloadable weights (OpenMDW-1.1)
| Measure | Weight | GLM-5V-Turbo | Trinity Large Thinking |
|---|---|---|---|
| Price | 50% | 37 | 69 |
| Inputs & features | 30% | 80 | 35 |
| Context window | 20% | 32 | 49 |
| Overall | 100% | 49/100 | 55/100 |
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) | Trinity Large ThinkingArcee AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $1.20 | $0.25 (best) |
| Output | $4.00 | $0.80 (best) |
| Cached input | $0.24 | $0.06 (best) |
| Blended (3:1) | $1.90 | $0.388 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Official Arcee API |
| Limits | ||
| Context window | 200,000 tokens | 524,288 tokens (best) |
| Max output | 131,072 tokens | 262,144 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | Yes | No |
| Audio | No | No |
| Video | Yes | No |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| Structured output | No | No |
| Availability | ||
| Weights | Proprietary | OpenOpenMDW-1.1 |
| API model ID | glm-5v-turbo | trinity-large-thinking |
| API providers | 14 (best) | 6 |
| Released | Apr 1, 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-5V-Turbo$20.00
- Trinity Large Thinking$4.10
Which should you choose?
Which is better: GLM-5V-Turbo or Trinity Large Thinking?
Trinity Large Thinking is the better all-round choice, scoring 55/100 against GLM-5V-Turbo (49). It leads on price and context window. GLM-5V-Turbo wins 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-5V-Turbo or Trinity Large Thinking?
Trinity Large Thinking is cheaper at $0.25 input / $0.80 output per million tokens (official Arcee API price). GLM-5V-Turbo costs $1.20 input / $4.00 output per million tokens (official Z.AI API price). At a typical mix of three input tokens to one output token, that is $0.388 per million tokens for Trinity Large Thinking versus $1.90 for GLM-5V-Turbo (4.9× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-5V-Turbo has not been scored yet and Trinity Large Thinking has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-5V-Turbo and Trinity Large Thinking 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?
Trinity Large Thinking has the largest context window at 524,288 tokens, against 200,000 for GLM-5V-Turbo. Maximum output per response: GLM-5V-Turbo up to 131,072, Trinity Large Thinking up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GLM-5V-Turbo accepts text, images, PDFs and video; Trinity Large Thinking accepts text. GLM-5V-Turbo handles the widest range of inputs.
Are any of these open source?
Trinity Large Thinking publishes its weights (OpenMDW-1.1) and can be self-hosted; GLM-5V-Turbo is proprietary.
Which is newer?
GLM-5V-Turbo is the newest, released Apr 1, 2026. Trinity Large Thinking came out Apr 1, 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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