Helix 02 vs Bonsai 27B
At a Glance
| Compare | Helix 02Figure | Bonsai 27BPrismML |
|---|---|---|
| Pricing and Limits | ||
| Context windowMaximum documented tokens | Not reported | 262K |
| Model facts checked | Aug 29, 2026View model evidence → | Sep 18, 2026View model evidence → |
Available Benchmarks
Side-by-Side Facts
| Field | Helix 02 | Bonsai 27B |
|---|---|---|
| Developer | Figure | PrismML |
| Family | Helix | Bonsai 27b |
| Model | Helix 02 | Bonsai 27B |
| Version | 02 | Bonsai 27B |
| Lifecycle | active | active |
| Released | 2026-01-05 | 2026-07-04 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Robot state | Text, Image |
| Output modalities | Robot action | Text |
| Context window | Unknown | 262K |
| Total parameters | Unknown | 27B |
| Active parameters | Unknown | Unknown |
| License | Unknown | apache-2.0 |
| Open weights | No | Yes |
| API available | No | No |
| Self-hostable | No | Yes |
| Provider access | Unknown | Unknown |
| Capabilities | dexterous-manipulation, long-horizon-control, tactile-control, whole-body-control | chat, generation, reasoning, tools, vision |
| Base model | Unknown | Qwen3.6 27B |
| Effective bit width | Unknown | 1 bit per weight |
| Language model size | Unknown | 3.53 GiB |
| Weight format | Unknown | Binary Q1_0 |
| Robotics model type | Vision-language-action model | Unknown |
| Action representation | Full-body joint targets | Unknown |
| Control architecture | Semantic reasoning, visuomotor policy, and kHz whole-body controller | Unknown |
| Inference location | On device | Unknown |
| Native control rate (Hz) | Unknown | Unknown |
| Supported embodiments | Figure 03 | Unknown |
| Training data | Figure reports more than 1,000 hours of human motion data plus sim-to-real reinforcement learning for its whole-body controller. | Unknown |
Helix 02 Capabilities
Bonsai 27B Capabilities
Primary Evidence
Sources and Freshness
Questions
Helix 02 vs Bonsai 27B FAQs
Is Helix 02 or Bonsai 27B better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Helix 02 and Bonsai 27B, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Helix 02 or Bonsai 27B?+
Neither model has a directly sourced input price in this comparison. Neither model has a directly sourced output price in this comparison.
Which has a larger context window, Helix 02 or Bonsai 27B?+
Neither model has a larger sourced context window in this comparison. Helix 02 is — and Bonsai 27B is 262K.
Which performs better in benchmarks, Helix 02 or Bonsai 27B?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Helix 02 or Bonsai 27B be self-hosted?+
Bonsai 27B is the only model in this pair currently marked as self-hostable. Helix 02 is not marked open weight; Bonsai 27B is open weight.
Can Helix 02 and Bonsai 27B understand images?+
Helix 02 is documented with image input; Bonsai 27B is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Helix 02 or Bonsai 27B?+
Neither has a larger sourced maximum output. Helix 02 is — and Bonsai 27B is —.
Do Helix 02 and Bonsai 27B support reasoning and tool use?+
Helix 02: image input. Bonsai 27B: reasoning, tool calling, and image input. Feature support does not establish relative quality.
Which is available from more inference providers, Helix 02 or Bonsai 27B?+
Helix 02 has 0 sourced provider routes; Bonsai 27B has 0, a tie.
Which offers better value, Helix 02 or Bonsai 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.