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Meta vs Relace
Muse Spark is a general agentic model. Relace provides small, fast models for the apply, search and compaction steps that surround it in a coding agent.
By The Subconscious Team · Updated
Meta vs Relace: key differences
Relace does not compete with Meta for the main model slot. It trains small specialist models: relace-apply-3 merges a lazy edit into the original file at about 10,000 tokens per second with 128K of input and output, an agentic search model explores large codebases in parallel, and a compaction model runs at 50,000 tokens per second. Relace says apply runs over 3x faster and cheaper than having the big model rewrite the file. Meta's Muse Spark 1.3 would be that big model, with 1M context at $1.25 in and $4.25 out.
The pair covers each other's gaps. Relace returns an error past 128K tokens, so very large files need a fallback, and Muse Spark's 1M window can take that job. Relace's search and compaction keep the context Muse Spark reads small, trimming input cost. Relace also offers self-hosted deployment for enterprises that keep code in-house, which matters since Meta's API is hosted only. Meta additionally ships Muse Glimmer weights, a self-hostable option for the main model.
What Meta and Relace do
Meta
Meta has moved from open Llama releases toward its own closed API. Meta Superintelligence Labs builds the Muse family, and in July 2026 Meta launched the Meta Model API with Muse Spark 1.1, a multimodal reasoning model aimed at agentic coding, tool use and computer use. At Meta Connect in September, Meta made the API generally available globally. Muse Spark 1.3 has a 1M token context and costs $1.25 in and $4.25 out per million tokens, with cached input at $0.15. Muse Wonder, released October 12, 2026, sits above it for longer, harder agent work at $4 in and $20 out, also with 1M context. The endpoint speaks OpenAI Chat Completions, Anthropic Messages and a stateful agentic format.
Example models: Muse Wonder, Muse Spark 1.3, Muse Spark Open
Full Meta profileRelace
Relace started out training small, fast models that act as tools for coding agents, and by October 2026 its homepage led with open-model inference instead. It says it served 30 trillion tokens in the 30 days to late October and ranks among the top providers on OpenRouter. The hosted catalog covers DeepSeek V4 Pro, V4 Flash and V4.1 Flash, Kimi K3, GLM 5.3, GLM 5.3 Flash and GLM 5.2 over OpenAI and Anthropic compatible APIs, billed per token with no subscription. Prices run from $0.07 in and $0.14 out per million tokens on DeepSeek V4 Flash to $2.00 in and $14.00 out on Kimi K3, and Relace says it reprices often.
Example models: DeepSeek V4.1 Flash, Kimi K3, GLM 5.3, relace-apply-3
Full Relace profileShould you choose Meta or Relace?
Meta vs Relace at a glance
| Attribute | Meta | Relace |
|---|---|---|
| Model access | Closed API; open Muse Spark Open and Glimmer | Open weights, plus specialist coding models |
| Flagship models | Muse Wonder, Muse Spark 1.3, Muse Spark Open | DeepSeek V4.1 Flash, Kimi K3, GLM 5.3, relace-apply-3 |
| Speed | ~145–233 tok/s on Muse Spark 1.3 | ~10,000 tok/s apply |
| Price | $1.25–$4 in, $4.25–$20 out; Contributor tier cheaper | $0.07 in, $0.50 out (DeepSeek V4.1 Flash) |
| Customization | Open Muse weights to fine-tune | Unknown |
| Deployment | Meta Model API, Oracle Cloud | Hosted API, OpenRouter or self-hosted |
| Long context | 1M | 128K on apply; varies by open model |
Frequently asked questions
What is the difference between Meta and Relace?
Muse Spark is a general agentic model. Relace provides small, fast models for the apply, search and compaction steps that surround it in a coding agent.
When should I choose Meta over Relace?
The main model that plans and writes code; A 1M context fallback for very large files; Tool use and computer use in one model.
When should I choose Relace over Meta?
Fast merges of lazy edits into source files; Parallel search over large repositories; Self-hosted code tooling for private repos.
Is Meta or Relace cheaper?
Meta: $1.25–$4 in, $4.25–$20 out; Contributor tier cheaper. Relace: $0.07 in, $0.50 out (DeepSeek V4.1 Flash). The cheaper choice depends on the model and workload.
Which has more context, Meta or Relace?
Meta: 1M. Relace: 128K on apply; varies by open model.
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If your agents run past 200K tokens, compare both against Subconscious. Our inference stack treats a long-horizon trace as the primary workload, so speed, cost, and accuracy hold up deep into the trace.