Bonsai 4B vs Grok 4.20 Multi Agent
At a Glance
| Compare |  Bonsai 4BPrismML | |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | UnrankedNot in the 46-model eligible cohort | #22 of 4663.4 score · 2/3 sources · provisional · missing LiveBench · full-core range 42.3–75.6 |
| Pricing and Limits | ||
| Input priceFrom · USD / 1M tokens | Not reported | $1.25Xai ↗ · Sep 3, 2026 |
| Output priceFrom · USD / 1M tokens | Not reported | $2.50Xai ↗ · Sep 3, 2026 |
| Context windowMaximum documented tokens | 33K | 1,000K |
| Model facts checked | Sep 18, 2026View model evidence → | Aug 29, 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 | Bonsai 4B | Grok 4.20 Multi-Agent |
|---|---|---|
| Developer | PrismML | xAI |
| Family | Bonsai 4b | Grok 4 20 |
| Model | Bonsai 4B | Grok 4.20 Multi-Agent |
| Version | Bonsai 4B | Grok 4.20 Multi-Agent |
| Lifecycle | active | preview |
| Released | 2026-03-29 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text | Text, Image |
| Output modalities | Text | Text |
| Context window | 33K | 1,000K |
| Total parameters | 4B | Unknown |
| Active parameters | Unknown | Unknown |
| License | apache-2.0 | Unknown |
| Open weights | Yes | No |
| API available | No | Yes |
| Self-hostable | Yes | No |
| Provider access | Unknown | Xai (Standard) |
| Capabilities | chat, generation | generation, reasoning, research, tools |
| Effective bit width | 1 bit per weight | Unknown |
| Weight size | 0.57 GB | Unknown |
| Weight format | Binary Q1_0 | Unknown |
Bonsai 4B Capabilities
Grok 4.20 Multi Agent Capabilities
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Primary Evidence
Sources and Freshness
Questions
Bonsai 4B vs Grok 4.20 Multi Agent FAQs
Is Bonsai 4B or Grok 4.20 Multi Agent better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Bonsai 4B and Grok 4.20 Multi Agent, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Bonsai 4B or Grok 4.20 Multi Agent?+
Only Grok 4.20 Multi Agent has a directly sourced input price: $1.25 per million tokens. Only Grok 4.20 Multi Agent has a directly sourced output price: $2.50 per million tokens.
Which has a larger context window, Bonsai 4B or Grok 4.20 Multi Agent?+
Grok 4.20 Multi Agent has the larger sourced context window. Bonsai 4B supports 33K and Grok 4.20 Multi Agent supports 1,000K.
Which performs better in benchmarks, Bonsai 4B or Grok 4.20 Multi Agent?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Bonsai 4B or Grok 4.20 Multi Agent be self-hosted?+
Bonsai 4B is the only model in this pair currently marked as self-hostable. Bonsai 4B is open weight; Grok 4.20 Multi Agent is not marked open weight.
Can Bonsai 4B and Grok 4.20 Multi Agent understand images?+
Bonsai 4B is not documented with image input; Grok 4.20 Multi Agent is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Bonsai 4B or Grok 4.20 Multi Agent?+
Neither has a larger sourced maximum output. Bonsai 4B is — and Grok 4.20 Multi Agent is —.
Do Bonsai 4B and Grok 4.20 Multi Agent support reasoning and tool use?+
Bonsai 4B: none of these features are definitively sourced. Grok 4.20 Multi Agent: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Bonsai 4B or Grok 4.20 Multi Agent?+
Bonsai 4B has 0 sourced provider routes; Grok 4.20 Multi Agent has 1, so Grok 4.20 Multi Agent has broader tracked availability.
Which offers better value, Bonsai 4B or Grok 4.20 Multi Agent?+
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.