Magnum v4 72B vs Ternary Bonsai 2 27B
Ternary Bonsai 2 27B costs 10.0x less per output token than Magnum v4 72B ($0.50 vs $5.00 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $5.00
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.50
Magnum v4 72B or Ternary Bonsai 2 27B: which to pick
Neither model has a coding score yet, so the two cannot be ranked on coding.
Compare them on price, context and the boards below.
No benchmark has tested either model yet, so price and context are the only way to compare them.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Neither has a coding score yet.
One side not measured
Long documents
Listed context window
Ternary Bonsai 2 27B
Ternary Bonsai 2 27B takes 262K tokens against 33K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ternary Bonsai 2 27B
Magnum v4 72B $0.0050, Ternary Bonsai 2 27B $0.0003 per turn.
List prices
At a glance
- Coding index
- Magnum v4 72B not benchmarked, Ternary Bonsai 2 27B not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Magnum v4 72B $5.00 against Ternary Bonsai 2 27B $0.50 per million output tokens, 10.0x apart.
- Context window
- Magnum v4 72B takes 33K tokens, Ternary Bonsai 2 27B 262K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Ternary Bonsai 2 27B costs less
Repository review
50K input + 3K output tokens
Ternary Bonsai 2 27B costs less
Agent loop
200K input + 10K output tokens
Ternary Bonsai 2 27B costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Magnum v4 72B | PrismML Ternary Bonsai 2 27B |
|---|---|---|
| Maker | Anthracite | Prism-ml |
| Weights | Open weights | Open weights |
| Released | October 22, 2024 | September 18, 2026 |
| Context window | 33K | 262K |
| Input $/Mtok | $2.50 | $0.075 |
| Output $/Mtok | $5.00 | $0.50 |
| Coding index | Not benchmarked | Not benchmarked |
| Independent measurements behind it | 0 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Magnum v4 72B better than Ternary Bonsai 2 27B for coding?
Neither model has a coding score yet, so the two cannot be ranked on coding. Compare them on price, context and the boards below.
Which is cheaper, Magnum v4 72B or Ternary Bonsai 2 27B?
Magnum v4 72B costs $2.50 per million input tokens and $5.00 per million output tokens; Ternary Bonsai 2 27B costs $0.075 and $0.50. Cost per solved task is known for neither of them.
Which has the bigger context window, Magnum v4 72B or Ternary Bonsai 2 27B?
Ternary Bonsai 2 27B, with 262K tokens against 33K.
Has any benchmark tested both Magnum v4 72B and Ternary Bonsai 2 27B?
No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 23, 2026.