Rnj-1 Instruct vs Granite-4.0-H-Small
Granite-4.0-H-Small comes out ahead, 61 to 50 on our weighted score, and it is the cheaper option too.
Essential AI
Rnj-1 Instruct
50/100- ECI—
- Price$0.15 / $0.15
- Context33K
- Our pick
IBMGranite-4.0-H-Small
61/100- ECI—
- Price$0.064 / $0.265
- Context131K
Add a model
Make it a three-way comparison.
Granite-4.0-H-Small is our pick
Granite-4.0-H-Small is the better all-round choice, scoring 61/100 against 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 · Rnj-1 Instruct $0.15 per 1M tokens (3:1 blend)
- Longest contextGranite-4.0-H-SmallGranite-4.0-H-Small 131,072 · Rnj-1 Instruct 32,768 tokens
- Widest inputsSame inputsRnj-1 Instruct: Text · Granite-4.0-H-Small: Text
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Rnj-1 Instruct | Granite-4.0-H-Small |
|---|---|---|---|
| Price | 50% | 85 | 91 |
| Inputs & features | 30% | 25 | 35 |
| Context window | 20% | 0 | 25 |
| Overall | 100% | 50/100 | 61/100 |
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 | Rnj-1 InstructEssential AI | Granite-4.0-H-SmallIBM |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.15 | $0.064 (best) |
| Output | $0.15 (best) | $0.265 |
| Cached input | — | — |
| Blended (3:1) | $0.15 | $0.114 (best) |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official watsonx.ai API |
| Limits | ||
| Context window | 32,768 tokens | 131,072 tokens (best) |
| Max output | 32,768 tokens | 131,072 tokens (best) |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | No |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | OpenApache 2.0 | Open |
| API model ID | — | ibm/granite-4-h-small |
| API providers | 1 | 1 |
| Released | Dec 4, 2025 | Oct 2, 2025 |
| Knowledge cutoff | — | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Rnj-1 Instruct$1.80
- Granite-4.0-H-Small$1.17
Which should you choose?
Which is better: Rnj-1 Instruct or Granite-4.0-H-Small?
Granite-4.0-H-Small is the better all-round choice, scoring 61/100 against 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, Rnj-1 Instruct or Granite-4.0-H-Small?
Granite-4.0-H-Small is cheaper at $0.064 input / $0.265 output per million tokens (official watsonx.ai API price). 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 $0.15 for Rnj-1 Instruct (1.3× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers both models yet. Rnj-1 Instruct has not been scored yet and Granite-4.0-H-Small has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Rnj-1 Instruct and Granite-4.0-H-Small 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 has the largest context window at 131,072 tokens, against 32,768 for Rnj-1 Instruct. Maximum output per response: Rnj-1 Instruct up to 32,768, Granite-4.0-H-Small up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Rnj-1 Instruct accepts text; Granite-4.0-H-Small accepts text. They handle the same number of input types.
Are any of these open source?
Yes, both publish their weights (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.
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.
