Helix 02 vs Grok 4.20 Multi Agent
At a Glance
| Compare | Helix 02Figure | |
|---|---|---|
| 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 | ||
| Context windowMaximum documented tokens | Not reported | 1,000K |
| Model facts checked | Aug 29, 2026View model evidence → | Aug 29, 2026View model evidence → |
Available Benchmarks
Side-by-Side Facts
| Field | Helix 02 | Grok 4.20 Multi-Agent |
|---|---|---|
| Developer | Figure | xAI |
| Family | Helix | Grok 4 20 |
| Model | Helix 02 | Grok 4.20 Multi-Agent |
| Version | 02 | Grok 4.20 Multi-Agent |
| Lifecycle | active | preview |
| Released | 2026-01-05 | Unknown |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image, Robot state | Text, Image |
| Output modalities | Robot action | Text |
| Context window | Unknown | 1,000K |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | No | Yes |
| Self-hostable | No | No |
| Provider access | Unknown | Xai (Standard) |
| Capabilities | dexterous-manipulation, long-horizon-control, tactile-control, whole-body-control | generation, reasoning, research, tools |
| 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
Grok 4.20 Multi Agent Capabilities
Primary Evidence
Sources and Freshness
Questions
Helix 02 vs Grok 4.20 Multi Agent FAQs
Is Helix 02 or Grok 4.20 Multi Agent better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Helix 02 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, Helix 02 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, Helix 02 or Grok 4.20 Multi Agent?+
Neither model has a larger sourced context window in this comparison. Helix 02 is — and Grok 4.20 Multi Agent is 1,000K.
Which performs better in benchmarks, Helix 02 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 Helix 02 or Grok 4.20 Multi Agent be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Helix 02 is not marked open weight; Grok 4.20 Multi Agent is not marked open weight.
Can Helix 02 and Grok 4.20 Multi Agent understand images?+
Helix 02 is 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, Helix 02 or Grok 4.20 Multi Agent?+
Neither has a larger sourced maximum output. Helix 02 is — and Grok 4.20 Multi Agent is —.
Do Helix 02 and Grok 4.20 Multi Agent support reasoning and tool use?+
Helix 02: image input. 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, Helix 02 or Grok 4.20 Multi Agent?+
Helix 02 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, Helix 02 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.