MiniMax M3 vs Bonsai Image Ternary 4B
At a Glance
| Compare | MiniMax M3MiniMax | Bonsai Image Ternary 4BPrismML |
|---|---|---|
| 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 | Not reported |
| Output priceFrom · USD / 1M tokens | $1.10Deepinfra ↗ · Sep 21, 2026 | Not reported |
| Context windowMaximum documented tokens | 1,049K | Not reported |
| 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 | Bonsai Image Ternary 4B |
|---|---|---|
| Developer | MiniMax | PrismML |
| Family | Minimax M3 | Bonsai Image 4b |
| Model | MiniMax-M3 | Bonsai Image Ternary 4B |
| Version | MiniMax-M3 | Bonsai Image Ternary 4B |
| Lifecycle | active | active |
| Released | 2026-06-01 | 2026-05-21 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text |
| Output modalities | Text | Image |
| Context window | 1,049K | Unknown |
| Total parameters | 427B | 4B |
| Active parameters | 23B | Unknown |
| License | other | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | No |
| Self-hostable | Yes | Yes |
| Provider access | Deepinfra (Standard), Fireworks Ai (Standard), Hugging Face (Standard), Openrouter (Standard), Together Ai (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, tools | generation |
| Base model | Unknown | FLUX.2 Klein 4B |
| Default resolution | Unknown | 512 × 512 |
| Transformer size | Unknown | 1.21 GB |
| Weight format | Unknown | Ternary weights with FP16 group scales |
MiniMax M3 Capabilities
Bonsai Image Ternary 4B Capabilities
Primary Evidence
Sources and Freshness
Questions
MiniMax M3 vs Bonsai Image Ternary 4B FAQs
Is MiniMax M3 or Bonsai Image Ternary 4B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both MiniMax M3 and Bonsai Image Ternary 4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, MiniMax M3 or Bonsai Image Ternary 4B?+
Only MiniMax M3 has a directly sourced input price: $0.28 per million tokens. Only MiniMax M3 has a directly sourced output price: $1.10 per million tokens.
Which has a larger context window, MiniMax M3 or Bonsai Image Ternary 4B?+
Neither model has a larger sourced context window in this comparison. MiniMax M3 is 1,049K and Bonsai Image Ternary 4B is —.
Which performs better in benchmarks, MiniMax M3 or Bonsai Image Ternary 4B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can MiniMax M3 or Bonsai Image Ternary 4B be self-hosted?+
Both models have the same recorded self-hosting status: supported. MiniMax M3 is open weight; Bonsai Image Ternary 4B is open weight.
Can MiniMax M3 and Bonsai Image Ternary 4B understand images?+
MiniMax M3 is documented with image input; Bonsai Image Ternary 4B is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, MiniMax M3 or Bonsai Image Ternary 4B?+
Neither has a larger sourced maximum output. MiniMax M3 is — and Bonsai Image Ternary 4B is —.
Do MiniMax M3 and Bonsai Image Ternary 4B support reasoning and tool use?+
MiniMax M3: reasoning, tool calling, and image input. Bonsai Image Ternary 4B: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, MiniMax M3 or Bonsai Image Ternary 4B?+
MiniMax M3 has 5 sourced provider routes; Bonsai Image Ternary 4B has 0, so MiniMax M3 has broader tracked availability.
Which offers better value, MiniMax M3 or Bonsai Image Ternary 4B?+
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.