Granite-4.0-H-Small vs GLM-4.5-Flash
Too close to call on our weighted score (GLM-4.5-Flash 65, Granite-4.0-H-Small 63). The right pick depends on what you value most.
IBMGranite-4.0-H-Small
63/100- ECI—
- Price$0.064 / $0.265
- Context131K
Z.ai (Zhipu)GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
Add a model
Make it a three-way comparison.
Too close to call
It is close. Our weighted score puts them within 3 points (GLM-4.5-Flash 65/100, Granite-4.0-H-Small 63/100), so choose by what matters most for your work: GLM-4.5-Flash on price. 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 priceGLM-4.5-FlashGLM-4.5-Flash Free · Granite-4.0-H-Small $0.114 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGranite-4.0-H-Small 131,072 · GLM-4.5-Flash 131,072 tokens
- Widest inputsSame inputsGranite-4.0-H-Small: Text · GLM-4.5-Flash: Text
- Self-hostingGranite-4.0-H-SmallPublishes downloadable weights
| Measure | Weight | Granite-4.0-H-Small | GLM-4.5-Flash |
|---|---|---|---|
| Price | 50% | 95 | 100 |
| Inputs & features | 30% | 35 | 35 |
| Context window | 20% | 24 | 24 |
| Overall | 100% | 63/100 | 65/100 |
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 | Granite-4.0-H-SmallIBM | GLM-4.5-FlashZ.ai (Zhipu) |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.064 | Free (best) |
| Output | $0.265 | Free (best) |
| Cached input | — | — |
| Blended (3:1) | $0.114 | Free (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Official watsonx.ai API | Official Z.AI API |
| Limits | ||
| Context window | 131,072 tokens | 131,072 tokens |
| Max output | 131,072 tokens (best) | 98,304 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | Yes |
| Tool calling | Yes | Yes |
| Structured output | Yes | No |
| Availability | ||
| Weights | Open | Proprietary |
| API model ID | ibm/granite-4-h-small | glm-4.5-flash |
| API providers | 1 | 4 (best) |
| Released | Oct 2, 2025 | Jul 28, 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.
- Granite-4.0-H-Small$1.17
- GLM-4.5-FlashFree
Which should you choose?
Which is better: Granite-4.0-H-Small or GLM-4.5-Flash?
It is close. Our weighted score puts them within 3 points (GLM-4.5-Flash 65/100, Granite-4.0-H-Small 63/100), so choose by what matters most for your work: GLM-4.5-Flash on price. 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, Granite-4.0-H-Small or GLM-4.5-Flash?
GLM-4.5-Flash is cheaper at Free input / Free output per million tokens (official Z.AI API price). Granite-4.0-H-Small costs $0.064 input / $0.265 output per million tokens (official watsonx.ai API price). GLM-4.5-Flash is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Granite-4.0-H-Small has not been scored yet and GLM-4.5-Flash has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Granite-4.0-H-Small and GLM-4.5-Flash 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?
Granite-4.0-H-Small and GLM-4.5-Flash share the same 131,072-token context window. Maximum output per response: Granite-4.0-H-Small up to 131,072, GLM-4.5-Flash up to 98,304 tokens.
Which can read images, PDFs, audio or video?
Granite-4.0-H-Small accepts text; GLM-4.5-Flash accepts text. They handle the same number of input types.
Are any of these open source?
Granite-4.0-H-Small publishes its weights and can be self-hosted; GLM-4.5-Flash is proprietary.
Which is newer?
Granite-4.0-H-Small is the newest, released Oct 2, 2025. GLM-4.5-Flash came out Jul 28, 2025. Knowledge cutoff: GLM-4.5-Flash 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 Oct 4, 2026.
