Claude Haiku 4.5 vs Helix 02
At a Glance
| Compare | Claude Haiku 4.5Anthropic | Helix 02Figure |
|---|---|---|
| Intelligence, Cost, and Efficiency | ||
| IntelligenceHigher is better · MM Intelligence v2.5 | #43 of 469.0 score · 2/3 sources · provisional · missing LiveBench · full-core range 6.0–39.3 | UnrankedNot in the 46-model eligible cohort |
| Pricing and Limits | ||
| Context windowMaximum documented tokens | 200K | Not reported |
| Model facts checked | Aug 28, 2026View model evidence → | Aug 29, 2026View model evidence → |
Available Benchmarks
Side-by-Side Facts
| Field | Claude Haiku 4.5 | Helix 02 |
|---|---|---|
| Developer | Anthropic | Figure |
| Family | Claude 4 5 | Helix |
| Model | Claude Haiku 4.5 | Helix 02 |
| Version | Claude Haiku 4.5 | 02 |
| Lifecycle | active | active |
| Released | 2025-10-15 | 2026-01-05 |
| Knowledge cutoff | Unknown | Unknown |
| Input modalities | Text, Image | Text, Image, Robot state |
| Output modalities | Text | Robot action |
| Context window | 200K | Unknown |
| Total parameters | Unknown | Unknown |
| Active parameters | Unknown | Unknown |
| License | Unknown | Unknown |
| Open weights | No | No |
| API available | Yes | No |
| Self-hostable | No | No |
| Provider access | Anthropic (Standard), Deepinfra (Standard) | Unknown |
| Capabilities | chat, generation, reasoning, tools | dexterous-manipulation, long-horizon-control, tactile-control, whole-body-control |
| Robotics model type | Unknown | Vision-language-action model |
| Action representation | Unknown | Full-body joint targets |
| Control architecture | Unknown | Semantic reasoning, visuomotor policy, and kHz whole-body controller |
| Inference location | Unknown | On device |
| Native control rate (Hz) | Unknown | Unknown |
| Supported embodiments | Unknown | Figure 03 |
| Training data | Unknown | Figure reports more than 1,000 hours of human motion data plus sim-to-real reinforcement learning for its whole-body controller. |
Claude Haiku 4.5 Capabilities
Helix 02 Capabilities
Primary Evidence
Sources and Freshness
Questions
Claude Haiku 4.5 vs Helix 02 FAQs
Is Claude Haiku 4.5 or Helix 02 better for coding?+
This comparison does not currently contain a protocol-matched coding benchmark for both Claude Haiku 4.5 and Helix 02, so Model Markets cannot name a coding leader from pricing, context size, or capability labels alone.
Which is cheaper, Claude Haiku 4.5 or Helix 02?+
Only Claude Haiku 4.5 has a directly sourced input price: $1.00 per million tokens. Only Claude Haiku 4.5 has a directly sourced output price: $5.00 per million tokens.
Which has a larger context window, Claude Haiku 4.5 or Helix 02?+
Neither model has a larger sourced context window in this comparison. Claude Haiku 4.5 is 200K and Helix 02 is —.
Which performs better in benchmarks, Claude Haiku 4.5 or Helix 02?+
There is no overall benchmark winner: At least two independently verified, protocol-matched benchmarks are required for an overall winner.
Can Claude Haiku 4.5 or Helix 02 be self-hosted?+
Both models have the same recorded self-hosting status: unsupported. Claude Haiku 4.5 is not marked open weight; Helix 02 is not marked open weight.
Can Claude Haiku 4.5 and Helix 02 understand images?+
Claude Haiku 4.5 is documented with image input; Helix 02 is documented with image input. This reflects supported input modalities, not vision quality.
Which can generate longer answers, Claude Haiku 4.5 or Helix 02?+
Neither has a larger sourced maximum output. Claude Haiku 4.5 is 64K and Helix 02 is —.
Do Claude Haiku 4.5 and Helix 02 support reasoning and tool use?+
Claude Haiku 4.5: reasoning, tool calling, and image input. Helix 02: image input. Feature support does not establish relative quality.
Which is available from more inference providers, Claude Haiku 4.5 or Helix 02?+
Claude Haiku 4.5 has 2 sourced provider routes; Helix 02 has 0, so Claude Haiku 4.5 has broader tracked availability.
Which offers better value, Claude Haiku 4.5 or Helix 02?+
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.