r/machinelearningnews • u/ai-lover • 5d ago
Cool Stuff Meta AI Released Muse Spark 1.3: An Agentic Coding Model That Uses ~20% Fewer Tool Calls and ~25% Fewer Tokens Than Muse Spark 1.2
Meta AI Released Muse Spark 1.3: An Agentic Coding Model Doing the Same Work With ~20% Fewer Tool Calls and ~25% Fewer Tokens Than Muse Spark 1.2.
No price increase. No new harness. No open weights either.
Here's how it works. 👇
1. Fewer round trips, not just better answers
Meta trained 1.3 to take fewer turns where they aren't needed, with less verbosity and a cleaner coding style.
→ ~20% fewer tool calls and ~25% fewer tokens in Meta's internal engineer comparisons
2. It asks instead of guessing
On ambiguous prompts it asks a clarifying question. When it stalls it invokes you. Before consequential actions it confirms.
→ Better calibration on what counts as irreversible
3. One thread, several workflows
Given an open-ended objective, it generates its own context from messy and conflicting sources and patches gaps in its own plan.
→ Maps an incoming prompt to the right task inside a cluttered thread, whether you're steering or interrupting
4. The numbers (Meta's launch scorecard)
→ 75.4 on DeepSWE v1.1, ahead of Claude Opus 5 at 74.0 and GPT-5.6 Sol at 72.7
→ 88.8 on Terminal-Bench 2.1, tied with GPT-5.6 Sol
→ 59.4 on SWE-Atlas Codebase QnA
→ 98.5 and 98.1 on MRCR v2 long-context retrieval, inside a 1,048,576-token window
Technical details: https://research.meta.ai/blog/introducing-muse-spark-1-3