Neither wins outright: PrismML: Ternary Bonsai 2 9B is the pick when cost matters at scale, Qwen: Qwen3 VL 30B A3B Thinking when you generate long outputs in one go.
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)
PrismML: Ternary Bonsai 2 9B
Qwen: Qwen3 VL 30B A3B Thinking
Difference
Customer-support chatbot
50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens)
$8.60
$41.75
PrismML: Ternary Bonsai 2 9B saves $33.15
RAG search over documents
20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens)
$10.90
$44.80
PrismML: Ternary Bonsai 2 9B saves $33.90
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)
$11.16
$46.80
PrismML: Ternary Bonsai 2 9B saves $35.64
Batch summarisation
10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens)
$7.18
$29.20
PrismML: Ternary Bonsai 2 9B saves $22.02
Long-document analysis
500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens)
$4.13
$15.50
PrismML: Ternary Bonsai 2 9B saves $11.37
Capabilities side by side
Capability
PrismML: Ternary Bonsai 2 9B
Qwen: Qwen3 VL 30B A3B Thinking
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
—
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
PrismML: Ternary Bonsai 2 9B: price unchanged since we started tracking it on 2026-10-28.
cost matters at scale — it is 80% cheaper on a typical 3:1 input/output mix ($8.60 vs $41.75 a month for 50,000 support chats)
you need seed (reproducible sampling) — to repeat a generation for tests and evals; Qwen: Qwen3 VL 30B A3B Thinking does not advertise it
you need log-probabilities — to read token confidence for classification and scoring; Qwen: Qwen3 VL 30B A3B Thinking does not advertise it
you want the newer model — released 2026-10-16, 13 months after the other
Choose Qwen: Qwen3 VL 30B A3B Thinking if…
you generate long outputs in one go — up to 236K tokens (about 176,900 words) per response
Frequently asked questions
Is PrismML: Ternary Bonsai 2 9B better than Qwen: Qwen3 VL 30B A3B Thinking?
Neither wins outright: PrismML: Ternary Bonsai 2 9B is the pick when cost matters at scale, Qwen: Qwen3 VL 30B A3B Thinking when you generate long outputs in one go. In short: PrismML: Ternary Bonsai 2 9B when cost matters at scale, you need seed (reproducible sampling), you need log-probabilities, you want the newer model; Qwen: Qwen3 VL 30B A3B Thinking when you generate long outputs in one go.
Which is cheaper, PrismML: Ternary Bonsai 2 9B or Qwen: Qwen3 VL 30B A3B Thinking?
PrismML: Ternary Bonsai 2 9B is cheaper: $0.09 vs $0.47 per 1M tokens at a typical 3:1 input/output mix, 80% less. For 50,000 support conversations a month that is $8.60 against $41.75.
How much do PrismML: Ternary Bonsai 2 9B and Qwen: Qwen3 VL 30B A3B Thinking cost per million tokens?
PrismML: Ternary Bonsai 2 9B costs $0.08 per 1M input tokens and $0.13 per 1M output tokens; Qwen: Qwen3 VL 30B A3B Thinking costs $0.29 input and $1.00 output. Output tokens are billed separately, so long answers shift the gap.
Which has the bigger context window, PrismML: Ternary Bonsai 2 9B or Qwen: Qwen3 VL 30B A3B Thinking?
Both take 262K tokens per request — roughly 393 pages of text.
Do PrismML: Ternary Bonsai 2 9B and Qwen: Qwen3 VL 30B A3B Thinking support function calling and JSON output?
Can PrismML: Ternary Bonsai 2 9B or Qwen: Qwen3 VL 30B A3B Thinking read images?
Yes, both accept image input.
Is PrismML: Ternary Bonsai 2 9B or Qwen: Qwen3 VL 30B A3B Thinking free to use?
No free variant is listed for either; both are pay-per-token.
What is the maximum output length of PrismML: Ternary Bonsai 2 9B and Qwen: Qwen3 VL 30B A3B Thinking?
PrismML: Ternary Bonsai 2 9B can write up to 66K tokens (about 49,200 words) per response; Qwen: Qwen3 VL 30B A3B Thinking up to 236K (about 176,900 words).
When were PrismML: Ternary Bonsai 2 9B and Qwen: Qwen3 VL 30B A3B Thinking released?
PrismML: Ternary Bonsai 2 9B was listed on 2026-10-16; Qwen: Qwen3 VL 30B A3B Thinking on 2025-10-06.
Has the price of PrismML: Ternary Bonsai 2 9B or Qwen: Qwen3 VL 30B A3B Thinking changed?
PrismML: Ternary Bonsai 2 9B: price unchanged since we started tracking it on 2026-10-28. Qwen: Qwen3 VL 30B A3B Thinking: input price raised 31% ($0.20 → $0.29/1M), output price cut 58% ($2.40 → $1.00/1M) on 2026-10-10 (3 price changes since 2026-03-10).
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...
Qwen3-VL-30B-A3B-Thinking is a multimodal model that unifies strong text generation with visual understanding for images and videos. Its Thinking variant enhances reasoning in STEM, math, and complex tasks. It excels...