MiniMax M3 vs Ternary Bonsai 2 27B
At a Glance
| Compare |  MiniMax M3MiniMax |  Ternary Bonsai 2 27BPrismML |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #35 of 4632.6 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 21.8–55.1 | UnrankedNot in the 46-model eligible cohort |
| CostLower is better · Published-token output estimate | #3 of 44$0.017 per LiveBench case | UnrankedNot in the 44-model eligible cohort |
| EfficiencyHigher is better · MM Efficiency v1.5 | #10 of 3859.2 score · 2/3 sources · provisional · missing ARC-AGI-2 · full-core range 53.8–70.4 | UnrankedNot in the 38-model eligible cohort |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.28Deepinfra ↗ · Sep 21, 2026 | $0.075Openrouter ↗ · Sep 22, 2026 |
| Output priceFrom · USD / 1M tokens | $1.10Deepinfra ↗ · Sep 21, 2026 | $0.50Openrouter ↗ · Sep 22, 2026 |
| Context windowMaximum documented tokens | 1,049K | 262K |
| Model facts checked | Aug 28, 2026View model evidence → | Sep 18, 2026View model evidence → |
Token prices are the lowest available sourced USD rates; input and output may use different providers. Cost ranking estimates output spend on LiveBench, not a full request bill. Ranking methodology →
Available Benchmarks
Side-by-Side Facts
| Field | MiniMax-M3 | Ternary Bonsai 2 27B |
|---|---|---|
| Developer | MiniMax | PrismML |
| Family | Minimax M3 | Bonsai 2 |
| Model | MiniMax-M3 | Ternary Bonsai 2 27B |
| Version | MiniMax-M3 | Ternary Bonsai 2 27B |
| Lifecycle | active | active |
| Released | 2026-06-01 | 2026-09-17 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image |
| Output modalities | Text | Text |
| Context window | 1,049K | 262K |
| Total parameters | 427B | 27.4B |
| Active parameters | 23B | Unknown |
| License | other | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | Yes |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Openrouter (Standard) |
| Capabilities | chat, generation, reasoning, tools | chat, generation, reasoning, tools, vision |
| Base model | Unknown | Qwen3.8 27B |
| Effective bit width | Unknown | 1.76 bits per weight |
| Language model size | Unknown | 5.93 GB |
| Weight format | Unknown | Ternary g128 with FP16 group scales |
MiniMax M3 Capabilities
Ternary Bonsai 2 27B Capabilities
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Primary Evidence
Sources and Freshness
Questions
MiniMax M3 vs Ternary Bonsai 2 27B FAQs
Is MiniMax M3 or Ternary Bonsai 2 27B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both MiniMax M3 and Ternary Bonsai 2 27B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, MiniMax M3 or Ternary Bonsai 2 27B?+
MiniMax M3 is $0.28 and Ternary Bonsai 2 27B is $0.075 per million tokens, so Ternary Bonsai 2 27B is cheaper on this metric. MiniMax M3 is $1.10 and Ternary Bonsai 2 27B is $0.50 per million tokens, so Ternary Bonsai 2 27B is cheaper on this metric.
Which has a larger context window, MiniMax M3 or Ternary Bonsai 2 27B?+
MiniMax M3 has the larger sourced context window. MiniMax M3 supports 1,049K and Ternary Bonsai 2 27B supports 262K.
Which performs better in benchmarks, MiniMax M3 or Ternary Bonsai 2 27B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can MiniMax M3 or Ternary Bonsai 2 27B be self-hosted?+
Both models have the same recorded self-hosting status: supported. MiniMax M3 is open weight; Ternary Bonsai 2 27B is open weight.
Can MiniMax M3 and Ternary Bonsai 2 27B understand images?+
MiniMax M3 is documented with image input; Ternary Bonsai 2 27B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, MiniMax M3 or Ternary Bonsai 2 27B?+
Neither has a larger sourced maximum output. MiniMax M3 is — and Ternary Bonsai 2 27B is —.
Do MiniMax M3 and Ternary Bonsai 2 27B support reasoning and tool use?+
MiniMax M3: reasoning, tool calling, and image input. Ternary Bonsai 2 27B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, MiniMax M3 or Ternary Bonsai 2 27B?+
MiniMax M3 has 5 sourced provider routes; Ternary Bonsai 2 27B has 1, so MiniMax M3 has broader tracked availability.
Which offers better value, MiniMax M3 or Ternary Bonsai 2 27B?+
There is no universal value winner. Compare the input and output prices above with the matched benchmark result for your workload: cheaper tokens can be offset by different quality, token usage, latency, or provider availability.