ZMIME
Comparison · 3 models · Updated Nov 2, 2026

Granite-4.0-H-Small vs Ministral 3 8B vs Rnj-1 Instruct

Ministral 3 8B comes out ahead, 68 to 61 and 50 on our weighted score, though Granite-4.0-H-Small is 24% cheaper per token.

  1. IBM

    Granite-4.0-H-Small

    Released Oct 2, 2025

    61/100
    • ECI—
    • Price$0.064 / $0.265
    • Context131K
  2. Our pick

    Mistral AI

    Ministral 3 8B

    Released Dec 2, 2025

    68/100
    • ECI—
    • Price$0.15 / $0.15
    • Context262K
  3. Essential AI

    Rnj-1 Instruct

    Released Dec 4, 2025

    50/100
    • ECI—
    • Price$0.15 / $0.15
    • Context33K
01 — Verdict

Ministral 3 8B is our pick

Ministral 3 8B is the better all-round choice, scoring 68/100 against Granite-4.0-H-Small (61) and Rnj-1 Instruct (50). It leads on inputs & features and context window. Granite-4.0-H-Small wins on price. 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 · Ministral 3 8B $0.15 · Rnj-1 Instruct $0.15 per 1M tokens (3:1 blend)
  • Longest contextMinistral 3 8BMinistral 3 8B 262,144 · Granite-4.0-H-Small 131,072 · Rnj-1 Instruct 32,768 tokens
  • Widest inputsMinistral 3 8BGranite-4.0-H-Small: Text · Ministral 3 8B: Text, Images · Rnj-1 Instruct: Text
  • Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
How the score is built
MeasureWeightGranite-4.0-H-SmallMinistral 3 8BRnj-1 Instruct
Price50%918585
Inputs & features30%356025
Context window20%25370
Overall100%61/10068/10050/100

Left out because at least one model lacks the data: capability. The remaining weights were rescaled.

02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

Granite-4.0-H-Small vs Ministral 3 8B vs Rnj-1 Instruct specifications side by side
SpecificationGranite-4.0-H-SmallIBMMinistral 3 8BMistral AIRnj-1 InstructEssential AI
Capability
Capabilities Index (ECI)———
ECI rank———
Price per million tokens
Input$0.064 (best)$0.15$0.15
Output$0.265$0.15 (best)$0.15 (best)
Cached input—$0.015—
Blended (3:1)$0.114 (best)$0.15$0.15
Long-context rateSame rateSame rateSame rate
Price sourceOfficial watsonx.ai APIOfficial Mistral APIMedian of 1 providers
Limits
Context window131,072 tokens262,144 tokens (best)32,768 tokens
Max output131,072 tokens262,144 tokens (best)32,768 tokens
Inputs and features
TextYesYesYes
ImagesNoYesNo
PDFsNoNoNo
AudioNoNoNo
VideoNoNoNo
ReasoningNoNoNo
Tool callingYesYesYes
Structured outputYesYesNo
Availability
WeightsOpenOpenApache 2.0OpenApache 2.0
API model IDibm/granite-4-h-smallministral-8b-2512—
API providers111 (best)1
ReleasedOct 2, 2025Dec 2, 2025Dec 4, 2025
Knowledge cutoff———
03 — Cost

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
  • Ministral 3 8B$1.80
  • Rnj-1 Instruct$1.80
04 — Questions

Which should you choose?

Which is better: Granite-4.0-H-Small, Ministral 3 8B or Rnj-1 Instruct?

Ministral 3 8B is the better all-round choice, scoring 68/100 against Granite-4.0-H-Small (61) and Rnj-1 Instruct (50). It leads on inputs & features and context window. Granite-4.0-H-Small wins on price. 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, Ministral 3 8B or Rnj-1 Instruct?

Granite-4.0-H-Small is cheaper at $0.064 input / $0.265 output per million tokens (official watsonx.ai API price). Ministral 3 8B costs $0.15 input / $0.15 output per million tokens (official Mistral 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 Ministral 3 8B (1.3× 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, Ministral 3 8B has not been scored yet and Rnj-1 Instruct has not been scored yet.

Which is better for coding?

There are no published SWE-bench Verified results for Granite-4.0-H-Small, Ministral 3 8B and Rnj-1 Instruct 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?

Ministral 3 8B has the largest context window at 262,144 tokens, against 131,072 for Granite-4.0-H-Small and 32,768 for Rnj-1 Instruct. Maximum output per response: Granite-4.0-H-Small up to 131,072, Ministral 3 8B up to 262,144, Rnj-1 Instruct up to 32,768 tokens.

Which can read images, PDFs, audio or video?

Granite-4.0-H-Small accepts text; Ministral 3 8B accepts text and images; Rnj-1 Instruct accepts text. Ministral 3 8B handles the widest range of inputs.

Are any of these open source?

Yes, all three 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. Ministral 3 8B came out Dec 2, 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.