Seed 2.0 Mini vs Bonsai Image Binary 4B
At a Glance
| Compare | Seed 2.0 MiniByteDance Seed |  Bonsai Image Binary 4BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.10Openrouter ↗ · Sep 22, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $0.40Openrouter ↗ · Sep 22, 2026 | Not reported |
| Context windowMaximum documented tokens | Not reported | Not reported |
| Model facts checked | Sep 3, 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 | Seed 2.0 Mini | Bonsai Image Binary 4B |
|---|---|---|
| Developer | ByteDance Seed | PrismML |
| Family | Seed 2 0 | Bonsai Image 4b |
| Model | Seed 2.0 Mini | Bonsai Image Binary 4B |
| Version | Seed 2.0 Mini | Bonsai Image Binary 4B |
| Lifecycle | active | active |
| Released | 2026-02-14 | 2026-05-18 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Video | Text |
| Output modalities | Text | Image |
| Context window | Unknown | Unknown |
| Total parameters | Unknown | 4B |
| Active parameters | Unknown | Unknown |
| License | Unknown | apache-2.0 |
| Open weights | No | Yes |
| API available | Yes | No |
| Self-hostable | No | Yes |
| Provider access | Openrouter (Standard) | Unknown |
| Capabilities | agents, chat, generation, reasoning, structured_outputs, tools | generation |
| Base model | Unknown | FLUX.2 Klein 4B |
| Default resolution | Unknown | 512 × 512 |
| Transformer size | Unknown | 0.93 GB |
| Weight format | Unknown | Binary weights with FP16 group scales |
Seed 2.0 Mini Capabilities
Bonsai Image Binary 4B Capabilities
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Primary Evidence
Sources and Freshness
Questions
Seed 2.0 Mini vs Bonsai Image Binary 4B FAQs
Is Seed 2.0 Mini or Bonsai Image Binary 4B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Seed 2.0 Mini and Bonsai Image Binary 4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Seed 2.0 Mini or Bonsai Image Binary 4B?+
Only Seed 2.0 Mini has a directly sourced input price: $0.10 per million tokens. Only Seed 2.0 Mini has a directly sourced output price: $0.40 per million tokens.
Which has a larger context window, Seed 2.0 Mini or Bonsai Image Binary 4B?+
Neither model has a larger sourced context window in this comparison. Seed 2.0 Mini is — and Bonsai Image Binary 4B is —.
Which performs better in benchmarks, Seed 2.0 Mini or Bonsai Image Binary 4B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Seed 2.0 Mini or Bonsai Image Binary 4B be self-hosted?+
Bonsai Image Binary 4B is the only model in this pair currently marked as self-hostable. Seed 2.0 Mini is not marked open weight; Bonsai Image Binary 4B is open weight.
Can Seed 2.0 Mini and Bonsai Image Binary 4B understand images?+
Seed 2.0 Mini is documented with image input; Bonsai Image Binary 4B is not documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Seed 2.0 Mini or Bonsai Image Binary 4B?+
Neither has a larger sourced maximum output. Seed 2.0 Mini is — and Bonsai Image Binary 4B is —.
Do Seed 2.0 Mini and Bonsai Image Binary 4B support reasoning and tool use?+
Seed 2.0 Mini: reasoning, tool calling, and image input. Bonsai Image Binary 4B: none of these features are definitively sourced. Feature support does not establish relative quality.
Which is available from more inference providers, Seed 2.0 Mini or Bonsai Image Binary 4B?+
Seed 2.0 Mini has 1 sourced provider route; Bonsai Image Binary 4B has 0, so Seed 2.0 Mini has broader tracked availability.
Which offers better value, Seed 2.0 Mini or Bonsai Image Binary 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.