Granite-4.0-H-Small vs Rnj-1 Instruct vs Apertus 8B
Granite-4.0-H-Small comes out ahead, 61 to 54 and 50 on our weighted score, and it is the cheaper option too.
- Our pick
IBMGranite-4.0-H-Small
61/100- ECI—
- Price$0.064 / $0.265
- Context131K
Essential AI
Rnj-1 Instruct
50/100- ECI—
- Price$0.15 / $0.15
- Context33K
Swiss AI
Apertus 8B
54/100- ECI—
- Price$0.10 / $0.20
- Context66K
Granite-4.0-H-Small is our pick
Granite-4.0-H-Small is the better all-round choice, scoring 61/100 against Apertus 8B (54) and Rnj-1 Instruct (50). 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 priceGranite-4.0-H-SmallGranite-4.0-H-Small $0.114 · Apertus 8B $0.125 · Rnj-1 Instruct $0.15 per 1M tokens (3:1 blend)
- Longest contextGranite-4.0-H-SmallGranite-4.0-H-Small 131,072 · Apertus 8B 65,536 · Rnj-1 Instruct 32,768 tokens
- Widest inputsSame inputsGranite-4.0-H-Small: Text · Rnj-1 Instruct: 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 | Rnj-1 Instruct | Apertus 8B |
|---|---|---|---|---|
| Price | 50% | 91 | 85 | 89 |
| Inputs & features | 30% | 35 | 25 | 25 |
| Context window | 20% | 25 | 0 | 12 |
| Overall | 100% | 61/100 | 50/100 | 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 | Rnj-1 InstructEssential AI | Apertus 8BSwiss AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $0.064 (best) | $0.15 | $0.10 |
| Output | $0.265 | $0.15 (best) | $0.20 |
| Cached input | — | — | — |
| Blended (3:1) | $0.114 (best) | $0.15 | $0.125 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Official watsonx.ai API | Median of 1 providers | Median of 1 providers |
| Limits | |||
| Context window | 131,072 tokens (best) | 32,768 tokens | 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 | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Open | OpenApache 2.0 | OpenApache-2.0 |
| API model ID | ibm/granite-4-h-small | — | — |
| API providers | 1 | 1 | 1 |
| Released | Oct 2, 2025 | Dec 4, 2025 | 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
- Rnj-1 Instruct$1.80
- Apertus 8B$1.40
Which should you choose?
Which is better: Granite-4.0-H-Small, Rnj-1 Instruct or Apertus 8B?
Granite-4.0-H-Small is the better all-round choice, scoring 61/100 against Apertus 8B (54) and Rnj-1 Instruct (50). 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, Granite-4.0-H-Small, Rnj-1 Instruct or Apertus 8B?
Granite-4.0-H-Small is cheaper at $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); Rnj-1 Instruct costs $0.15 input / $0.15 output per million tokens (median across 1 API provider). At a typical mix of three input tokens to one output token, that is $0.114 per million tokens for Granite-4.0-H-Small versus $0.125 for Apertus 8B (1.1× as much) and $0.15 for Rnj-1 Instruct (1.3× 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, Rnj-1 Instruct 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, Rnj-1 Instruct 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?
Granite-4.0-H-Small has the largest context window at 131,072 tokens, against 65,536 for Apertus 8B and 32,768 for Rnj-1 Instruct. Maximum output per response: Granite-4.0-H-Small up to 131,072, Rnj-1 Instruct 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; Rnj-1 Instruct 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 (Apache 2.0 and Apache-2.0), so you can self-host them.
Which is newer?
Rnj-1 Instruct is the newest, released Dec 4, 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.
