Rnj-1 Instruct vs Voxtral Small 24B 2507
Voxtral Small 24B 2507 comes out ahead, 55 to 50 on our weighted score, though Rnj-1 Instruct is 14% cheaper per token.
Essential AI
Rnj-1 Instruct
50/100- ECI—
- Price$0.15 / $0.15
- Context33K
- Our pick
Mistral AIVoxtral Small 24B 2507
55/100- ECI—
- Price$0.10 / $0.40
- Context33K
Add a model
Make it a three-way comparison.
Voxtral Small 24B 2507 is our pick
Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against Rnj-1 Instruct (50). It leads on inputs & features. Rnj-1 Instruct 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 priceRnj-1 InstructRnj-1 Instruct $0.15 · Voxtral Small 24B 2507 $0.175 per 1M tokens (3:1 blend)
- Longest contextAbout the sameRnj-1 Instruct 32,768 · Voxtral Small 24B 2507 32,768 tokens
- Widest inputsVoxtral Small 24B 2507Rnj-1 Instruct: Text · Voxtral Small 24B 2507: Text, Audio
- Self-hostingAll open weightsEvery model here can be downloaded and run on your own hardware
| Measure | Weight | Rnj-1 Instruct | Voxtral Small 24B 2507 |
|---|---|---|---|
| Price | 50% | 85 | 82 |
| Inputs & features | 30% | 25 | 45 |
| Context window | 20% | 0 | 0 |
| Overall | 100% | 50/100 | 55/100 |
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 | Voxtral Small 24B 2507Mistral AI |
|---|---|---|
| Capability | ||
| Capabilities Index (ECI) | — | — |
| ECI rank | — | — |
| Price per million tokens | ||
| Input | $0.15 | $0.10 (best) |
| Output | $0.15 (best) | $0.40 |
| Cached input | — | — |
| Blended (3:1) | $0.15 (best) | $0.175 |
| Long-context rate | Same rate | Same rate |
| Price source | Median of 1 providers | Official Mistral API |
| Limits | ||
| Context window | 32,768 tokens | 32,768 tokens |
| Max output | 32,768 tokens | 32,768 tokens |
| Inputs and features | ||
| Text | Yes | Yes |
| Images | No | No |
| PDFs | No | No |
| Audio | No | Yes |
| Video | No | No |
| Reasoning | No | No |
| Tool calling | Yes | Yes |
| Structured output | No | Yes |
| Availability | ||
| Weights | OpenApache 2.0 | OpenApache 2.0 |
| API model ID | — | voxtral-small-latest |
| API providers | 1 | 10 (best) |
| Released | Dec 4, 2025 | Jul 15, 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
- Voxtral Small 24B 2507$1.80
Which should you choose?
Which is better: Rnj-1 Instruct or Voxtral Small 24B 2507?
Voxtral Small 24B 2507 is the better all-round choice, scoring 55/100 against Rnj-1 Instruct (50). It leads on inputs & features. Rnj-1 Instruct 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, Rnj-1 Instruct or Voxtral Small 24B 2507?
Rnj-1 Instruct is cheaper at $0.15 input / $0.15 output per million tokens (median across 1 API provider). Voxtral Small 24B 2507 costs $0.10 input / $0.40 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.15 per million tokens for Rnj-1 Instruct versus $0.175 for Voxtral Small 24B 2507 (1.2× 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 Voxtral Small 24B 2507 has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Rnj-1 Instruct and Voxtral Small 24B 2507 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?
Rnj-1 Instruct and Voxtral Small 24B 2507 share the same 32,768-token context window. Maximum output per response: Rnj-1 Instruct up to 32,768, Voxtral Small 24B 2507 up to 32,768 tokens.
Which can read images, PDFs, audio or video?
Rnj-1 Instruct accepts text; Voxtral Small 24B 2507 accepts text and audio. Voxtral Small 24B 2507 handles the widest range of inputs.
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. Voxtral Small 24B 2507 came out Jul 15, 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.
Related comparisons
- Add Ministral 3 8BThree-way comparison
- Rnj-1 Instruct vs Ministral 3 8BMistral AI
- Rnj-1 Instruct vs MiMo-V2-FlashXiaomi
- Rnj-1 Instruct vs GLM-4.7-FlashXZ.ai (Zhipu)
- Rnj-1 Instruct vs Step 3.5 FlashStepFun
- Voxtral Small 24B 2507 vs Gemini 2.5 Flash-LiteGoogle
- Voxtral Small 24B 2507 vs Qwen FlashAlibaba (Qwen)
