GLM-4.5-Flash vs Granite-4.0-H-Micro vs PaddleOCR VL
GLM-4.5-Flash comes out ahead, 65 to 62 and 62 on our weighted score, and it is the cheaper option too.
- Our pick
Z.ai (Zhipu)GLM-4.5-Flash
65/100- ECI—
- PriceFree / Free
- Context131K
IBMGranite-4.0-H-Micro
62/100- ECI—
- Price$0.018 / $0.115
- Context131K
PaddlePaddle
PaddleOCR VL
62/100- ECI—
- Price$0.02 / $0.02
- Context131K
GLM-4.5-Flash is our pick
GLM-4.5-Flash is the better all-round choice, scoring 65/100 against Granite-4.0-H-Micro (62) and PaddleOCR VL (62). 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 priceGLM-4.5-FlashGLM-4.5-Flash Free · PaddleOCR VL $0.02 · Granite-4.0-H-Micro $0.042 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGLM-4.5-Flash 131,072 · Granite-4.0-H-Micro 131,072 · PaddleOCR VL 131,072 tokens
- Widest inputsPaddleOCR VLGLM-4.5-Flash: Text · Granite-4.0-H-Micro: Text · PaddleOCR VL: Text, Images
- Self-hostingGranite-4.0-H-Micro and PaddleOCR VLPublishes downloadable weights (Apache-2.0)
| Measure | Weight | GLM-4.5-Flash | Granite-4.0-H-Micro | PaddleOCR VL |
|---|---|---|---|---|
| Price | 50% | 100 | 100 | 100 |
| Inputs & features | 30% | 35 | 25 | 25 |
| Context window | 20% | 25 | 25 | 25 |
| Overall | 100% | 65/100 | 62/100 | 62/100 |
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-4.5-FlashZ.ai (Zhipu) | Granite-4.0-H-MicroIBM | PaddleOCR VLPaddlePaddle |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | Free (best) | $0.018 | $0.02 |
| Output | Free (best) | $0.115 | $0.02 |
| Cached input | — | — | — |
| Blended (3:1) | Free (best) | $0.042 | $0.02 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official Z.AI API | Median of 2 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens | 131,072 tokens | 131,072 tokens |
| Max output | 98,304 tokens | 131,072 tokens (best) | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | No | No |
| Tool calling | Yes | Yes | No |
| Structured output | No | No | No |
| Availability | |||
| Weights | Proprietary | Open | OpenApache-2.0 |
| API model ID | glm-4.5-flash | — | — |
| API providers | 5 (best) | 2 | 1 |
| Released | Jul 28, 2025 | Oct 2, 2025 | Oct 16, 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-4.5-FlashFree
- Granite-4.0-H-Micro$0.405
- PaddleOCR VL$0.24
Which should you choose?
Which is better: GLM-4.5-Flash, Granite-4.0-H-Micro or PaddleOCR VL?
GLM-4.5-Flash is the better all-round choice, scoring 65/100 against Granite-4.0-H-Micro (62) and PaddleOCR VL (62). 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-4.5-Flash, Granite-4.0-H-Micro or PaddleOCR VL?
GLM-4.5-Flash is cheaper at Free input / Free output per million tokens (official Z.AI API price). PaddleOCR VL costs $0.02 input / $0.02 output per million tokens (median across 1 API provider); Granite-4.0-H-Micro costs $0.018 input / $0.115 output per million tokens (median across 2 API providers). GLM-4.5-Flash is listed as free.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. GLM-4.5-Flash has not been scored yet, Granite-4.0-H-Micro has not been scored yet and PaddleOCR VL has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GLM-4.5-Flash, Granite-4.0-H-Micro and PaddleOCR VL yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that PaddleOCR VL does not support tool calling, which most coding agents need.
Which has the bigger context window?
GLM-4.5-Flash, Granite-4.0-H-Micro and PaddleOCR VL share the same 131,072-token context window. Maximum output per response: GLM-4.5-Flash up to 98,304, Granite-4.0-H-Micro up to 131,072, PaddleOCR VL up to 16,384 tokens.
Which can read images, PDFs, audio or video?
GLM-4.5-Flash accepts text; Granite-4.0-H-Micro accepts text; PaddleOCR VL accepts text and images. PaddleOCR VL handles the widest range of inputs.
Are any of these open source?
Granite-4.0-H-Micro and PaddleOCR VL publishes its weights (Apache-2.0) and can be self-hosted; GLM-4.5-Flash is proprietary.
Which is newer?
PaddleOCR VL is the newest, released Oct 16, 2025. Granite-4.0-H-Micro came out 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 Nov 2, 2026.
