MiniMax M2.7 vs Ternary Bonsai 2 27B
Ternary Bonsai 2 27B costs 2.4x less per output token than MiniMax M2.7 ($0.50 vs $1.20 per million). Updated October 23, 2026; no benchmark has tested both models yet.
- Coding
- 36.2
- Overall
- 44.5
- Output $/M
- $1.20
- Coding
- No data
- Overall
- No data
- Output $/M
- $0.50
MiniMax M2.7 or Ternary Bonsai 2 27B: which to pick
Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Ternary Bonsai 2 27B has none, so the two cannot be ranked on coding.
Pick Ternary Bonsai 2 27B for output tokens 2.4x cheaper ($0.50 vs $1.20 per million) and a larger context window (262K against 205K tokens).
No benchmark has tested both yet. MiniMax M2.7 has results on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI); 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
Only MiniMax M2.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only MiniMax M2.7 has a AA Intelligence Index result, 22.8.
Directional only
Agentic work
AA Agentic Index
No call
Only MiniMax M2.7 has a AA Agentic Index result, 15.3.
Directional only
Reasoning
GPQA Diamond
No call
Only MiniMax M2.7 has a GPQA Diamond result, 86.6%.
Directional only
Math
AIME
No call
Only MiniMax M2.7 has a AIME result, 91.0%.
Directional only
Knowledge
MMLU Pro
No call
Only MiniMax M2.7 has a MMLU Pro result, 80.4%.
Directional only
Web design
Design Arena: websites
No call
Only MiniMax M2.7 has a Design Arena: websites result, 1242.
Directional only
Long documents
Listed context window
Ternary Bonsai 2 27B
Ternary Bonsai 2 27B takes 262K tokens against 205K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Ternary Bonsai 2 27B
MiniMax M2.7 $0.0009, Ternary Bonsai 2 27B $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only MiniMax M2.7 has the number, $0.64.
Directional only
At a glance
- Coding index
- MiniMax M2.7 36.2 from 3 benchmarks, 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
- MiniMax M2.7 $1.20 against Ternary Bonsai 2 27B $0.50 per million output tokens, 2.4x apart.
- Context window
- MiniMax M2.7 takes 205K 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 Index17 boards measured
| Benchmark | MiniMax M2.7 | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| LMArena WebDev | 1398 | Not measured | Only MiniMax M2.7 measured |
| AA Coding Index | 52.6 | Not measured | Only MiniMax M2.7 measured |
| LiveCodeBench (Vals AI) | 79.9% | Not measured | Only MiniMax M2.7 measured |
| SWE-bench Verified (Vals AI) | 73.8% | Not measured | Only MiniMax M2.7 measured |
| Vibe Code Bench (Vals AI) | 11.9% | Not measured | Only MiniMax M2.7 measured |
| Code migration (Vals AI) | 8.7% | Not measured | Only MiniMax M2.7 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only MiniMax M2.7 measured |
| Terminal-Bench 2.1 (Vals AI) | 48.7% | Not measured | Only MiniMax M2.7 measured |
| SciCode | 50.1% | Not measured | Only MiniMax M2.7 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 39.4% | Not measured | Only MiniMax M2.7 measured |
| Terminal-Bench | 45.1% | Not measured | Only MiniMax M2.7 measured |
| WeirdML | 37.0% | Not measured | Only MiniMax M2.7 measured |
| ALE-Bench | 599.3 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: coding | 1454 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: software and IT | 1445 | Not measured | Only MiniMax M2.7 measured |
| LMArena WebDev: React | 1388 | Not measured | Only MiniMax M2.7 measured |
| LMArena WebDev: HTML | 1402 | Not measured | Only MiniMax M2.7 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 | MiniMax M2.7 | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| AA Intelligence Index | 22.8 | Not measured | Only MiniMax M2.7 measured |
| Epoch Capabilities Index | 145.8 | Not measured | Only MiniMax M2.7 measured |
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | MiniMax M2.7 | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| AA Agentic Index | 15.3 | Not measured | Only MiniMax M2.7 measured |
| Finance Agent (Vals AI) | 27.9% | Not measured | Only MiniMax M2.7 measured |
| Tax Agent Bench (Vals AI) | 6.9% | Not measured | Only MiniMax M2.7 measured |
| Legal Research Bench (Vals AI) | 10.6% | Not measured | Only MiniMax M2.7 measured |
| Excel Modeling Benchmark (Vals AI) | 28.4% | Not measured | Only MiniMax M2.7 measured |
| τ²-Bench Telecom | 84.8% | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 36 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards measured
| Benchmark | MiniMax M2.7 | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| GPQA Diamond | 86.6% | Not measured | Only MiniMax M2.7 measured |
| GPQA Diamond (Artificial Analysis run) | 87.4% | Not measured | Only MiniMax M2.7 measured |
| Humanity's Last Exam (Artificial Analysis run) | 29.6% | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: hard prompts | 1423 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: expert | 1443 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: hard prompts in English | 1441 | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 17 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
| Benchmark | MiniMax M2.7 | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| AIME | 91.0% | Not measured | Only MiniMax M2.7 measured |
| ProofBench | 3.0% | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: math | 1421 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: mathematical work | 1437 | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 10 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index10 boards measured
| Benchmark | MiniMax M2.7 | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| MMLU Pro | 80.4% | Not measured | Only MiniMax M2.7 measured |
| LegalBench (Vals AI) | 84.0% | Not measured | Only MiniMax M2.7 measured |
| CaseLaw (Vals AI) | 60.9% | Not measured | Only MiniMax M2.7 measured |
| CorpFin (Vals AI) | 61.2% | Not measured | Only MiniMax M2.7 measured |
| TaxEval (Vals AI) | 66.6% | Not measured | Only MiniMax M2.7 measured |
| MedCode (Vals AI) | 34.4% | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: science | 1416 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: medicine and healthcare | 1409 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: legal and government | 1403 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: business and finance | 1407 | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 10 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards measured
| Benchmark | MiniMax M2.7 | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| Design Arena: websites | 1242 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: UI components | 1208 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: game dev | 1209 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: data viz | 1233 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: 3D | 1194 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: all code categories | 1233 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: SVG | 1136 | Not measured | Only MiniMax M2.7 measured |
| Design Arena: ASCII art | 1136 | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 1 board here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index21 boards measured
| Benchmark | MiniMax M2.7 | Ternary Bonsai 2 27B | Leader |
|---|---|---|---|
| MedScribe (Vals AI) | 79.9% | Not measured | Only MiniMax M2.7 measured |
| IFBench | 75.7% | Not measured | Only MiniMax M2.7 measured |
| Long context reasoning (AA-LCR) | 78.3% | Not measured | Only MiniMax M2.7 measured |
| ExploitBench | 13.3% | Not measured | Only MiniMax M2.7 measured |
| LMArena Text | 1405 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: instruction following | 1405 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: creative writing | 1354 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: English | 1426 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: non-English | 1383 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Chinese | 1441 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: German | 1398 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Japanese | 1259 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Korean | 1316 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: French | 1424 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Spanish | 1403 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Russian | 1384 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: Polish | 1388 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: multi-turn | 1412 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: longer queries | 1419 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: writing and language | 1376 | Not measured | Only MiniMax M2.7 measured |
| LMArena Text: entertainment and media | 1361 | Not measured | Only MiniMax M2.7 measured |
| Neither model has a result on the other 27 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 | MiniMax M2.7 | PrismML Ternary Bonsai 2 27B |
|---|---|---|
| Maker | MiniMax | Prism-ml |
| Weights | Open weights | Open weights |
| Released | March 18, 2026 | September 18, 2026 |
| Context window | 205K | 262K |
| Input $/Mtok | $0.30 | $0.075 |
| Output $/Mtok | $1.20 | $0.50 |
| Coding index | 36.2 | Not benchmarked |
| Independent measurements behind it | 3 | 0 |
| Cost per solved task | $0.64 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is MiniMax M2.7 better than Ternary Bonsai 2 27B for coding?
Only MiniMax M2.7 has a coding score, 36.2 on the Vibe Coding Index; Ternary Bonsai 2 27B has none, so the two cannot be ranked on coding. Pick Ternary Bonsai 2 27B for output tokens 2.4x cheaper ($0.50 vs $1.20 per million) and a larger context window (262K against 205K tokens).
Which is cheaper, MiniMax M2.7 or Ternary Bonsai 2 27B?
MiniMax M2.7 costs $0.30 per million input tokens and $1.20 per million output tokens; Ternary Bonsai 2 27B costs $0.075 and $0.50. Cost per solved task is known for MiniMax M2.7 only.
Which has the bigger context window, MiniMax M2.7 or Ternary Bonsai 2 27B?
Ternary Bonsai 2 27B, with 262K tokens against 205K.
Has any benchmark tested both MiniMax M2.7 and Ternary Bonsai 2 27B?
No benchmark has tested both yet. MiniMax M2.7 has results on LMArena WebDev, AA Coding Index and LiveCodeBench (Vals AI); Ternary Bonsai 2 27B has none yet. Compare them on price and context instead. Data as of October 23, 2026.