o3 Mini vs Ternary Bonsai 2 27B
Ternary Bonsai 2 27B costs 8.8x less per output token than o3 Mini ($0.50 vs $4.40 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- 38.0
- Output $/M
- $4.40
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.50
o3 Mini 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 both yet. o3 Mini has results on Aider polyglot, SWE-bench Verified and SWE-bench Lite; Ternary Bonsai 2 27B has none yet. Compare them on price and context instead.
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
Intelligence
AA Intelligence Index
No call
Only o3 Mini has a AA Intelligence Index result, 12.5.
Directional only
Reasoning
GPQA Diamond
No call
Only o3 Mini has a GPQA Diamond result, 75.5%.
Directional only
Math
AIME
No call
Only o3 Mini has a AIME result, 86.5%.
Directional only
Knowledge
MMLU Pro
No call
Only o3 Mini has a MMLU Pro result, 78.7%.
Directional only
Long documents
Listed context window
Ternary Bonsai 2 27B
Ternary Bonsai 2 27B takes 262K tokens against 200K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ternary Bonsai 2 27B
o3 Mini $0.0033, Ternary Bonsai 2 27B $0.0003 per turn.
List prices
At a glance
- Coding index
- o3 Mini 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
- o3 Mini $4.40 against Ternary Bonsai 2 27B $0.50 per million output tokens, 8.8x apart.
- Context window
- o3 Mini takes 200K 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.
CodingDirectional onlySix of these boards feed the Vibe Coding Index13 boards measured
| Benchmark | o3 Mini | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| Aider polyglot | 60.4% | Not measured | Only o3 Mini measured |
| SWE-bench Verified | 42.4% | Not measured | Only o3 Mini measured |
| SWE-bench Lite | 32.3% | Not measured | Only o3 Mini measured |
| LiveCodeBench (Vals AI) | 71.5% | Not measured | Only o3 Mini measured |
| LiveCodeBench (Artificial Analysis run) | 73.4% | Not measured | Only o3 Mini measured |
| SciCode | 42.8% | Not measured | Only o3 Mini measured |
| Terminal-Bench Hard (Artificial Analysis run) | 6.8% | Not measured | Only o3 Mini measured |
| GSO-Bench | 1.3% | Not measured | Only o3 Mini measured |
| WeirdML | 43.7% | Not measured | Only o3 Mini measured |
| Cybench | 22.5% | Not measured | Only o3 Mini measured |
| LMArena Text: coding | 1378 | Not measured | Only o3 Mini measured |
| LMArena Text: software and IT | 1364 | Not measured | Only o3 Mini measured |
| SciCode | 7.7% | Not measured | Only o3 Mini measured |
| Neither model has a result on the other 26 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
| Benchmark | o3 Mini | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 12.5 | Not measured | Only o3 Mini measured |
| Epoch Capabilities Index | 140.2 | Not measured | Only o3 Mini measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | o3 Mini | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| τ²-Bench Telecom | 31.3% | Not measured | Only o3 Mini measured |
| Neither model has a result on the other 40 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index12 boards measured
| Benchmark | o3 Mini | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| GPQA Diamond | 75.5% | Not measured | Only o3 Mini measured |
| GPQA Diamond (Artificial Analysis run) | 77.3% | Not measured | Only o3 Mini measured |
| Humanity's Last Exam (Artificial Analysis run) | 12.0% | Not measured | Only o3 Mini measured |
| GPQA Diamond (Epoch AI run) | 77.0% | Not measured | Only o3 Mini measured |
| ARC-AGI | 34.5% | Not measured | Only o3 Mini measured |
| ARC-AGI-2 | 3.0% | Not measured | Only o3 Mini measured |
| SimpleBench | 22.8% | Not measured | Only o3 Mini measured |
| Chess puzzles | 15.0% | Not measured | Only o3 Mini measured |
| Mystery game puzzles | 7.0% | Not measured | Only o3 Mini measured |
| LMArena Text: hard prompts | 1365 | Not measured | Only o3 Mini measured |
| LMArena Text: expert | 1364 | Not measured | Only o3 Mini measured |
| LMArena Text: hard prompts in English | 1375 | Not measured | Only o3 Mini measured |
| Neither model has a result on the other 10 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | o3 Mini | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| AIME | 86.5% | Not measured | Only o3 Mini measured |
| MATH 500 (Vals AI) | 91.8% | Not measured | Only o3 Mini measured |
| MGSM (Vals AI) | 91.3% | Not measured | Only o3 Mini measured |
| OTIS Mock AIME | 76.9% | Not measured | Only o3 Mini measured |
| FrontierMath, tiers 1 to 3 | 18.6% | Not measured | Only o3 Mini measured |
| FrontierMath, tier 4 | 0.0% | Not measured | Only o3 Mini measured |
| MATH level 5 | 96.5% | Not measured | Only o3 Mini measured |
| LMArena Text: math | 1396 | Not measured | Only o3 Mini measured |
| LMArena Text: mathematical work | 1399 | Not measured | Only o3 Mini measured |
| Neither model has a result on the other 4 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index11 boards measured
| Benchmark | o3 Mini | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| MMLU Pro | 78.7% | Not measured | Only o3 Mini measured |
| LegalBench (Vals AI) | 71.5% | Not measured | Only o3 Mini measured |
| CorpFin (Vals AI) | 45.3% | Not measured | Only o3 Mini measured |
| TaxEval (Vals AI) | 69.4% | Not measured | Only o3 Mini measured |
| MedQA (Vals AI) | 94.8% | Not measured | Only o3 Mini measured |
| MMLU Pro (Artificial Analysis run) | 80.2% | Not measured | Only o3 Mini measured |
| SimpleQA Verified | 15.3% | Not measured | Only o3 Mini measured |
| LMArena Text: science | 1339 | Not measured | Only o3 Mini measured |
| LMArena Text: medicine and healthcare | 1330 | Not measured | Only o3 Mini measured |
| LMArena Text: legal and government | 1328 | Not measured | Only o3 Mini measured |
| LMArena Text: business and finance | 1313 | Not measured | Only o3 Mini measured |
| Neither model has a result on the other 7 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index23 boards measured
| Benchmark | o3 Mini | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| IFBench | 67.1% | Not measured | Only o3 Mini measured |
| Long context reasoning (AA-LCR) | 43.0% | Not measured | Only o3 Mini measured |
| DTBench | 68.8% | Not measured | Only o3 Mini measured |
| LMCA | 19.0% | Not measured | Only o3 Mini measured |
| Fiction.LiveBench | 50.0% | Not measured | Only o3 Mini measured |
| Creative writing (Lech Mazur) | 61.7% | Not measured | Only o3 Mini measured |
| LMArena Text | 1337 | Not measured | Only o3 Mini measured |
| LMArena Text: instruction following | 1337 | Not measured | Only o3 Mini measured |
| LMArena Text: creative writing | 1286 | Not measured | Only o3 Mini measured |
| LMArena Text: English | 1351 | Not measured | Only o3 Mini measured |
| LMArena Text: non-English | 1319 | Not measured | Only o3 Mini measured |
| LMArena Text: Chinese | 1379 | Not measured | Only o3 Mini measured |
| LMArena Text: German | 1303 | Not measured | Only o3 Mini measured |
| LMArena Text: Japanese | 1286 | Not measured | Only o3 Mini measured |
| LMArena Text: Korean | 1313 | Not measured | Only o3 Mini measured |
| LMArena Text: French | 1334 | Not measured | Only o3 Mini measured |
| LMArena Text: Spanish | 1321 | Not measured | Only o3 Mini measured |
| LMArena Text: Russian | 1304 | Not measured | Only o3 Mini measured |
| LMArena Text: Polish | 1294 | Not measured | Only o3 Mini measured |
| LMArena Text: multi-turn | 1320 | Not measured | Only o3 Mini measured |
| LMArena Text: longer queries | 1343 | Not measured | Only o3 Mini measured |
| LMArena Text: writing and language | 1313 | Not measured | Only o3 Mini measured |
| LMArena Text: entertainment and media | 1283 | Not measured | Only o3 Mini measured |
| Neither model has a result on the other 23 boards here | |||
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 | OpenAI o3 Mini | PrismML Ternary Bonsai 2 27B |
|---|---|---|
| Maker | OpenAI | Prism-ml |
| Weights | No public weights listed | Open weights |
| Released | January 31, 2025 | September 18, 2026 |
| Context window | 200K | 262K |
| Input $/Mtok | $1.10 | $0.075 |
| Output $/Mtok | $4.40 | $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 o3 Mini 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, o3 Mini or Ternary Bonsai 2 27B?
o3 Mini costs $1.10 per million input tokens and $4.40 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, o3 Mini or Ternary Bonsai 2 27B?
Ternary Bonsai 2 27B, with 262K tokens against 200K.
Has any benchmark tested both o3 Mini and Ternary Bonsai 2 27B?
No benchmark has tested both yet. o3 Mini has results on Aider polyglot, SWE-bench Verified and SWE-bench Lite; Ternary Bonsai 2 27B has none yet. Compare them on price and context instead. Data as of October 22, 2026.