GLM-4.5V vs Morph V3 Fast
GLM-4.5V comes out ahead, 48 to 32 on our weighted score.
- Our pick
Z.ai (Zhipu)GLM-4.5V
48/100- ECI—
- Price$0.60 / $1.80
- Context64K
Morph
Morph V3 Fast
32/100- ECI—
- Price$0.80 / $1.20
- Context262K
Add a model
Make it a three-way comparison.
GLM-4.5V is our pick
GLM-4.5V is the better all-round choice, scoring 48/100 against Morph V3 Fast (32). It leads on inputs & features. Morph V3 Fast wins on 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 priceSame priceGLM-4.5V $0.90 · Morph V3 Fast $0.90 per 1M tokens (3:1 blend)
- Longest contextMorph V3 FastMorph V3 Fast 262,144 · GLM-4.5V 64,000 tokens
- Widest inputsGLM-4.5VGLM-4.5V: Text, Images, Video · Morph V3 Fast: Text
- Self-hostingGLM-4.5VPublishes downloadable weights
| Measure | Weight | GLM-4.5V | Morph V3 Fast |
|---|---|---|---|
| Price | 50% | 50 | 50 |
| Inputs & features | 30% | 70 | 0 |
| Context window | 20% | 12 | 37 |
| Overall | 100% | 48/100 | 32/100 |
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-4.5VZ.ai (Zhipu) | Morph V3 FastMorph |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.60 (best) | $0.80 |
| Output | $1.80 | $1.20 (best) |
| Cached input | $0.11 | — |
| Blended (3:1) | $0.90 | $0.90 |
| Long-context rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 5 providers |
| Limits | ||
| Context window | 64,000 tokens | 262,144 tokens (best) |
| Max output | 16,384 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | Yes | No |
| PDFs | No | No |
| Audio | No | No |
| Video | Yes | No |
| Reasoning | Yes | No |
| Tool calling | Yes | No |
| Structured output | No | No |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | glm-4.5v | — |
| API providers | 17 (best) | 5 |
| Released | Aug 11, 2025 | Jul 7, 2025 |
| Knowledge cutoff | Apr 2025 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GLM-4.5V$9.60
- Morph V3 Fast$10.40
Which should you choose?
Which is better: GLM-4.5V or Morph V3 Fast?
GLM-4.5V is the better all-round choice, scoring 48/100 against Morph V3 Fast (32). It leads on inputs & features. Morph V3 Fast wins on 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, GLM-4.5V or Morph V3 Fast?
GLM-4.5V and Morph V3 Fast cost the same: $0.60 input / $1.80 output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. GLM-4.5V has not been scored yet and Morph V3 Fast has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5V and Morph V3 Fast yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Morph V3 Fast does not support tool calling, which most coding agents need.
Which has the bigger context window?
Morph V3 Fast has the largest context window at 262,144 tokens, against 64,000 for GLM-4.5V. Maximum output per response: GLM-4.5V up to 16,384, Morph V3 Fast up to 131,072 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5V accepts text, images and video; Morph V3 Fast accepts text. GLM-4.5V handles the widest range of inputs.
Are any of these open source?
GLM-4.5V publishes its weights and can be self-hosted; Morph V3 Fast is proprietary.
Which is newer?
GLM-4.5V is the newest, released Aug 11, 2025. Morph V3 Fast came out Jul 7, 2025. Knowledge cutoff: GLM-4.5V Apr 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 Nov 2, 2026.
