Apertus 8B vs Granite-4.0-H-Small vs Qwen3 VL Flash (Alibaba Cloud)
Qwen3 VL Flash (Alibaba Cloud) comes out ahead, 72 to 61 and 54 on our weighted score, and it is the cheaper option too.
Swiss AI
Apertus 8B
54/100- ECI—
- Price$0.10 / $0.20
- Context66K
IBMGranite-4.0-H-Small
61/100- ECI—
- Price$0.064 / $0.265
- Context131K
- Our pick
Alibaba (Qwen)Qwen3 VL Flash (Alibaba Cloud)
72/100- ECI—
- Price$0.022 / $0.215
- Context262K
Qwen3 VL Flash (Alibaba Cloud) is our pick
Qwen3 VL Flash (Alibaba Cloud) is the better all-round choice, scoring 72/100 against Granite-4.0-H-Small (61) and Apertus 8B (54). It leads on price, inputs & features and 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 priceQwen3 VL Flash (Alibaba Cloud)Qwen3 VL Flash (Alibaba Cloud) $0.07 · Granite-4.0-H-Small $0.114 · Apertus 8B $0.125 per 1M tokens (3:1 blend)
- Longest contextQwen3 VL Flash (Alibaba Cloud)Qwen3 VL Flash (Alibaba Cloud) 262,144 · Granite-4.0-H-Small 131,072 · Apertus 8B 65,536 tokens
- Widest inputsQwen3 VL Flash (Alibaba Cloud)Apertus 8B: Text · Granite-4.0-H-Small: Text · Qwen3 VL Flash (Alibaba Cloud): Text, Images
- Self-hostingApertus 8B and Granite-4.0-H-SmallPublishes downloadable weights (Apache-2.0)
| Measure | Weight | Apertus 8B | Granite-4.0-H-Small | Qwen3 VL Flash (Alibaba Cloud) |
|---|---|---|---|---|
| Price | 50% | 89 | 91 | 100 |
| Inputs & features | 30% | 25 | 35 | 50 |
| Context window | 20% | 12 | 25 | 37 |
| Overall | 100% | 54/100 | 61/100 | 72/100 |
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 | Apertus 8BSwiss AI | Granite-4.0-H-SmallIBM | Qwen3 VL Flash (Alibaba Cloud)Alibaba (Qwen) |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.10 | $0.064 | $0.022 (best) |
| Output | $0.20 (best) | $0.265 | $0.215 |
| Cached input | — | — | — |
| Blended (3:1) | $0.125 | $0.114 | $0.07 (best) |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official watsonx.ai API | Median of 1 providers |
| Limits | |||
| Context window | 65,536 tokens | 131,072 tokens | 262,144 tokens (best) |
| Max output | 8,192 tokens | 131,072 tokens (best) | 32,768 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 | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | No |
| Availability | |||
| Weights | OpenApache-2.0 | Open | Proprietary |
| API model ID | — | ibm/granite-4-h-small | — |
| API providers | 1 | 1 | 1 |
| Released | Sep 2, 2025 | Oct 2, 2025 | Oct 15, 2025 |
| Knowledge cutoff | Sep 2025 | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Apertus 8B$1.40
- Granite-4.0-H-Small$1.17
- Qwen3 VL Flash (Alibaba Cloud)$0.65
Which should you choose?
Which is better: Apertus 8B, Granite-4.0-H-Small or Qwen3 VL Flash (Alibaba Cloud)?
Qwen3 VL Flash (Alibaba Cloud) is the better all-round choice, scoring 72/100 against Granite-4.0-H-Small (61) and Apertus 8B (54). It leads on price, inputs & features and 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, Apertus 8B, Granite-4.0-H-Small or Qwen3 VL Flash (Alibaba Cloud)?
Qwen3 VL Flash (Alibaba Cloud) is cheaper at $0.022 input / $0.215 output per million tokens (median across 1 API provider). Granite-4.0-H-Small costs $0.064 input / $0.265 output per million tokens (official watsonx.ai API price); Apertus 8B costs $0.10 input / $0.20 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.07 per million tokens for Qwen3 VL Flash (Alibaba Cloud) versus $0.114 for Granite-4.0-H-Small (1.6× as much) and $0.125 for Apertus 8B (1.8× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Apertus 8B has not been scored yet, Granite-4.0-H-Small has not been scored yet and Qwen3 VL Flash (Alibaba Cloud) has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Apertus 8B, Granite-4.0-H-Small and Qwen3 VL Flash (Alibaba Cloud) yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Qwen3 VL Flash (Alibaba Cloud) has the largest context window at 262,144 tokens, against 131,072 for Granite-4.0-H-Small and 65,536 for Apertus 8B. Maximum output per response: Apertus 8B up to 8,192, Granite-4.0-H-Small up to 131,072, Qwen3 VL Flash (Alibaba Cloud) up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Apertus 8B accepts text; Granite-4.0-H-Small accepts text; Qwen3 VL Flash (Alibaba Cloud) accepts text and images. Qwen3 VL Flash (Alibaba Cloud) handles the widest range of inputs.
Are any of these open source?
Apertus 8B and Granite-4.0-H-Small publishes its weights (Apache-2.0) and can be self-hosted; Qwen3 VL Flash (Alibaba Cloud) is proprietary.
Which is newer?
Qwen3 VL Flash (Alibaba Cloud) is the newest, released Oct 15, 2025. Granite-4.0-H-Small came out Oct 2, 2025; Apertus 8B came out Sep 2, 2025. Knowledge cutoff: Apertus 8B Sep 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.
