Qwen3 Coder Next vs Bonsai Image Binary 4B
At a Glance
| Compare |  Qwen3 Coder NextQwen |  Bonsai Image Binary 4BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | $0.12Openrouter ↗ · Sep 22, 2026 | Not reported |
| Output priceFrom · USD / 1M tokens | $0.80Openrouter ↗ · Sep 22, 2026 | Not reported |
| Context windowMaximum documented tokens | 262K | 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 | Qwen3-Coder-Next | Bonsai Image Binary 4B |
|---|---|---|
| Developer | Qwen | PrismML |
| Family | Qwen3 Coder Next | Bonsai Image 4b |
| Model | Qwen3-Coder-Next | Bonsai Image Binary 4B |
| Version | Qwen3-Coder-Next | Bonsai Image Binary 4B |
| Lifecycle | active | active |
| Released | 2026-02-02 | 2026-05-18 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text |
| Output modalities | Text | Image |
| Context window | 262K | Unknown |
| Total parameters | 79.7B | 4B |
| Active parameters | 3B | Unknown |
| License | apache-2.0 | apache-2.0 |
| Open weights | Yes | Yes |
| API available | Yes | No |
| Self-hostable | Yes | Yes |
| Provider access | Hugging Face (Standard), Openrouter (Standard) | Unknown |
| Capabilities | chat, generation, 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 |
Qwen3 Coder Next Capabilities
Bonsai Image Binary 4B Capabilities
Related Comparisons
| A | Pair | B | Context |
|---|---|---|---|
Qwen3-Coder-NextQwen | vs |  GPT-6 AstraOpenAI | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs | Claude Fable 5.1Anthropic | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs |  Gemini 3.1 ProGoogle DeepMind | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs |  DeepSeek-V4.1-FlashDeepSeek | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs | Grok 4.6xAI | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs | Qwen3.8-MaxQwen | family variantstext |
Qwen3-Coder-NextQwen | vs |  Kimi-K3Moonshot AI | cross-developer peerstext |
 MiniMax-M3MiniMax | vs | Qwen3-Coder-NextQwen | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs |  GLM-5.3Z.ai | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs |  Hy4 previewTencent | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs | Seed 2.1 ProByteDance Seed | cross-developer peerstext |
Qwen3-Coder-NextQwen | vs |  Mistral Large 3Mistral AI | cross-developer peerstext |
Primary Evidence
Sources and Freshness
Questions
Qwen3 Coder Next vs Bonsai Image Binary 4B FAQs
Is Qwen3 Coder Next or Bonsai Image Binary 4B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Qwen3 Coder Next and Bonsai Image Binary 4B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Qwen3 Coder Next or Bonsai Image Binary 4B?+
Only Qwen3 Coder Next has a directly sourced input price: $0.12 per million tokens. Only Qwen3 Coder Next has a directly sourced output price: $0.80 per million tokens.
Which has a larger context window, Qwen3 Coder Next or Bonsai Image Binary 4B?+
Neither model has a larger sourced context window in this comparison. Qwen3 Coder Next is 262K and Bonsai Image Binary 4B is —.
Which performs better in benchmarks, Qwen3 Coder Next 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 Qwen3 Coder Next or Bonsai Image Binary 4B be self-hosted?+
Both models have the same recorded self-hosting status: supported. Qwen3 Coder Next is open weight; Bonsai Image Binary 4B is open weight.
Can Qwen3 Coder Next and Bonsai Image Binary 4B understand images?+
Qwen3 Coder Next is not 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, Qwen3 Coder Next or Bonsai Image Binary 4B?+
Neither has a larger sourced maximum output. Qwen3 Coder Next is — and Bonsai Image Binary 4B is —.
Do Qwen3 Coder Next and Bonsai Image Binary 4B support reasoning and tool use?+
Qwen3 Coder Next: tool calling. 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, Qwen3 Coder Next or Bonsai Image Binary 4B?+
Qwen3 Coder Next has 2 sourced provider routes; Bonsai Image Binary 4B has 0, so Qwen3 Coder Next has broader tracked availability.
Which offers better value, Qwen3 Coder Next 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.