Granite-4.0-H-Small vs Ling 3.0 Flash vs Apertus 8B
Ling 3.0 Flash comes out ahead, 65 to 61 and 54 on our weighted score, and it is the cheaper option too.
IBMGranite-4.0-H-Small
61/100- ECI—
- Price$0.064 / $0.265
- Context131K
- Our pick
inclusionAILing 3.0 Flash
65/100- ECI—
- Price$0.06 / $0.18
- Context262K
Swiss AI
Apertus 8B
54/100- ECI—
- Price$0.10 / $0.20
- Context66K
Ling 3.0 Flash is our pick
Ling 3.0 Flash is the better all-round choice, scoring 65/100 against Granite-4.0-H-Small (61) and Apertus 8B (54). It leads on price 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 priceLing 3.0 FlashLing 3.0 Flash $0.09 · Granite-4.0-H-Small $0.114 · Apertus 8B $0.125 per 1M tokens (3:1 blend)
- Longest contextLing 3.0 FlashLing 3.0 Flash 262,144 · Granite-4.0-H-Small 131,072 · Apertus 8B 65,536 tokens
- Widest inputsSame inputsGranite-4.0-H-Small: Text · Ling 3.0 Flash: Text · Apertus 8B: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Granite-4.0-H-Small | Ling 3.0 Flash | Apertus 8B |
|---|---|---|---|---|
| Price | 50% | 91 | 95 | 89 |
| Inputs & features | 30% | 35 | 35 | 25 |
| Context window | 20% | 25 | 37 | 12 |
| Overall | 100% | 61/100 | 65/100 | 54/100 |
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 | Ling 3.0 FlashinclusionAI | Apertus 8BSwiss AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.064 | $0.06 (best) | $0.10 |
| Output | $0.265 | $0.18 (best) | $0.20 |
| Cached input | — | — | — |
| Blended (3:1) | $0.114 | $0.09 (best) | $0.125 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official watsonx.ai API | Median of 7 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens | 262,144 tokens (best) | 65,536 tokens |
| Max output | 131,072 tokens (best) | 32,768 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | OpenMIT | OpenApache-2.0 |
| API model ID | ibm/granite-4-h-small | — | — |
| API providers | 1 | 9 (best) | 1 |
| Released | Oct 2, 2025 | Jul 23, 2026 | Sep 2, 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.
- Granite-4.0-H-Small$1.17
- Ling 3.0 Flash$0.96
- Apertus 8B$1.40
Which should you choose?
Which is better: Granite-4.0-H-Small, Ling 3.0 Flash or Apertus 8B?
Ling 3.0 Flash is the better all-round choice, scoring 65/100 against Granite-4.0-H-Small (61) and Apertus 8B (54). It leads on price 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, Granite-4.0-H-Small, Ling 3.0 Flash or Apertus 8B?
Ling 3.0 Flash is cheaper at $0.06 input / $0.18 output per million tokens (median across 7 API providers). 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 $0.09 per million tokens for Ling 3.0 Flash versus $0.114 for Granite-4.0-H-Small (1.3× as much) and $0.125 for Apertus 8B (1.4× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Granite-4.0-H-Small has not been scored yet, Ling 3.0 Flash has not been scored yet and Apertus 8B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Granite-4.0-H-Small, Ling 3.0 Flash and Apertus 8B 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?
Ling 3.0 Flash 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: Granite-4.0-H-Small up to 131,072, Ling 3.0 Flash up to 32,768, Apertus 8B up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Granite-4.0-H-Small accepts text; Ling 3.0 Flash accepts text; Apertus 8B accepts text. They handle the same number of input types.
Are any of these open source?
Yes, all three publish their weights (MIT and Apache-2.0), so you can self-host them.
Which is newer?
Ling 3.0 Flash is the newest, released Jul 23, 2026. 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.
