Choose Mistral: Mistral Small 4 if…
- you generate long outputs in one go — up to 210K tokens (about 157,300 words) per response
Mistral: Mistral Small 4 vs PrismML: Ternary Bonsai 2 9B
Neither wins outright: Mistral: Mistral Small 4 is the pick when you generate long outputs in one go, PrismML: Ternary Bonsai 2 9B when cost matters at scale.
Key numbers
| Spec | Mistral: Mistral Small 4 | PrismML: Ternary Bonsai 2 9B |
|---|---|---|
| Provider | Mistral AI | Prism ML |
| Input price (per 1M tokens) | $0.15 | $0.08 |
| Output price (per 1M tokens) | $0.60 | $0.13 |
| Blended price (3:1 input/output) | $0.26 | $0.09 |
| Cheaper than … of all models we track | 65% | 82% |
| Context window | 262K tokens (~393 pages) | 262K tokens (~393 pages) |
| Larger context than … of all models | 47% | 47% |
| Max output per response | 210K tokens (~157,300 words) | 66K tokens (~49,200 words) |
| Input types | text, image | text, image |
| Output types | text | text |
| Free variant | No | No |
| Listed since | 2026-03-16 | 2026-10-16 |
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What it costs for real workloads
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | Mistral: Mistral Small 4 | PrismML: Ternary Bonsai 2 9B | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | $23.25 | $8.60 | PrismML: Ternary Bonsai 2 9B saves $14.65 |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | $24.00 | $10.90 | PrismML: Ternary Bonsai 2 9B saves $13.10 |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | $25.20 | $11.16 | PrismML: Ternary Bonsai 2 9B saves $14.04 |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | $15.60 | $7.18 | PrismML: Ternary Bonsai 2 9B saves $8.42 |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | $8.10 | $4.13 | PrismML: Ternary Bonsai 2 9B saves $3.97 |
Capabilities side by side
| Capability | Mistral: Mistral Small 4 | PrismML: Ternary Bonsai 2 9B | What it lets you do |
|---|---|---|---|
| Tool / function calling | ✓ Yes | ✓ Yes | call your APIs and run agent loops |
| Structured output (JSON schema) | ✓ Yes | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | ✓ Yes | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | ✓ Yes | ✓ Yes | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | — | — | accept documents without your own parsing step |
| Image output | — | — | generate images, not just text |
| Built-in web search | — | — | answer from live web results |
| Seed (reproducible sampling) | ✓ Yes | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | ✓ Yes | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
Price history
- Mistral: Mistral Small 4: price unchanged since we started tracking it on 2026-03-31.
- PrismML: Ternary Bonsai 2 9B: price unchanged since we started tracking it on 2026-10-28.
Which should you choose?
Choose PrismML: Ternary Bonsai 2 9B if…
- cost matters at scale — it is 65% cheaper on a typical 3:1 input/output mix ($8.60 vs $23.25 a month for 50,000 support chats)
- you need log-probabilities — to read token confidence for classification and scoring; Mistral: Mistral Small 4 does not advertise it
- you want the newer model — released 2026-10-16, 7 months after the other
Frequently asked questions
Is Mistral: Mistral Small 4 better than PrismML: Ternary Bonsai 2 9B?
Neither wins outright: Mistral: Mistral Small 4 is the pick when you generate long outputs in one go, PrismML: Ternary Bonsai 2 9B when cost matters at scale. In short: Mistral: Mistral Small 4 when you generate long outputs in one go; PrismML: Ternary Bonsai 2 9B when cost matters at scale, you need log-probabilities, you want the newer model.
Which is cheaper, Mistral: Mistral Small 4 or PrismML: Ternary Bonsai 2 9B?
PrismML: Ternary Bonsai 2 9B is cheaper: $0.09 vs $0.26 per 1M tokens at a typical 3:1 input/output mix, 65% less. For 50,000 support conversations a month that is $8.60 against $23.25.
How much do Mistral: Mistral Small 4 and PrismML: Ternary Bonsai 2 9B cost per million tokens?
Mistral: Mistral Small 4 costs $0.15 per 1M input tokens and $0.60 per 1M output tokens; PrismML: Ternary Bonsai 2 9B costs $0.08 input and $0.13 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, Mistral: Mistral Small 4 or PrismML: Ternary Bonsai 2 9B?
Both take 262K tokens per request — roughly 393 pages of text.
Do Mistral: Mistral Small 4 and PrismML: Ternary Bonsai 2 9B support function calling and JSON output?
Tool calling — Mistral: Mistral Small 4: yes, PrismML: Ternary Bonsai 2 9B: yes. JSON-schema structured output — Mistral: Mistral Small 4: yes, PrismML: Ternary Bonsai 2 9B: yes.
Can Mistral: Mistral Small 4 or PrismML: Ternary Bonsai 2 9B read images?
Yes, both accept image input.
Is Mistral: Mistral Small 4 or PrismML: Ternary Bonsai 2 9B free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of Mistral: Mistral Small 4 and PrismML: Ternary Bonsai 2 9B?
Mistral: Mistral Small 4 can write up to 210K tokens (about 157,300 words) per response; PrismML: Ternary Bonsai 2 9B up to 66K (about 49,200 words).
When were Mistral: Mistral Small 4 and PrismML: Ternary Bonsai 2 9B released?
Mistral: Mistral Small 4 was listed on 2026-03-16; PrismML: Ternary Bonsai 2 9B on 2026-10-16.
About the two models
Mistral: Mistral Small 4
Mistral Small 4 is the next major release in the Mistral Small family, unifying the capabilities of several flagship Mistral models into a single system. It combines strong reasoning from...
Full Mistral: Mistral Small 4 specs →PrismML: Ternary Bonsai 2 9B
Ternary Bonsai 2 9B is PrismML’s compact, open-weight language model for conversational AI, reasoning, and tool use. Built on Qwen3.5, it uses ternary weights packed into 2 bits for efficient...
Full PrismML: Ternary Bonsai 2 9B specs →