Both are Meta models. Muse Spark 1.3 is the newer, generally stronger default; reach for Muse Spark 1.1 when a specific cost or latency profile matters more than the latest capabilities.
Muse Spark 1.1 and Muse Spark 1.3 are both Meta models, so the real question is not which lab to trust but which tier fits your workload and budget. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Context window: 1M vs 1M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Long-context recall: Muse Spark 1.3 is far stronger at 1M tokens on MRCR v2 (54.1% vs 98.1%) — important if you actually fill the window with documents.
Recency: Muse Spark 1.3 is the newer model by about 55 days (released September 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Muse Spark 1.1
Muse Spark 1.3
Provider
Meta (US)
Meta (US)
Released
July 9, 2026
September 2, 2026
Context window
1M (~1,573 pages)
1M tokens (~1,500 pages)
Price (in/out)
$1.25/$4.25 per 1M tokens
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, image, video
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
54.1%
98.1%
Who wins what
Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported): Muse Spark 1.1 — Muse Spark 1.1 lists scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported) among its strengths; Muse Spark 1.3 does not.
Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck: Muse Spark 1.1 — Muse Spark 1.1 lists subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck among its strengths; Muse Spark 1.3 does not.
Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported): Muse Spark 1.1 — Muse Spark 1.1 lists professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported) among its strengths; Muse Spark 1.3 does not.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2: Muse Spark 1.3 — Muse Spark 1.1 is comparatively weak here — not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark
DeepSWE v1.1 long-horizon software engineering (75.4): Muse Spark 1.3 — Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it is the newer of the two.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1): Muse Spark 1.3 — Muse Spark 1.3 lists near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1) among its strengths; Muse Spark 1.1 does not.
Which should you pick?
Someone analysing very long documents or codebases: Muse Spark 1.1 — Larger 1M window fits more in one prompt.
Anyone whose priority is scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported): Muse Spark 1.1 — It is specifically built for that.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2: Muse Spark 1.3 — That is its strongest area.
Muse Spark 1.1: where it fits
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.
Its trade-offs are real: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Because Muse Spark 1.1 and Muse Spark 1.3 come from the same lab (Meta), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Muse Spark 1.3 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Muse Spark 1.3 and drop down only with a concrete reason.
Frequently asked questions
Is Muse Spark 1.1 or Muse Spark 1.3 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) while Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Spark 1.1 or Muse Spark 1.3?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Effectively neither — 1M vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Muse Spark 1.1 to Muse Spark 1.3?
Since both are Meta models, the newer one (Muse Spark 1.3) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Muse Spark 1.1 or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 55 days after Muse Spark 1.1.
Muse Spark 1.1 vs Muse Spark 1.3
Meta · US | Meta · US · Updated June 2026
Quick verdict
Both are Meta models. Muse Spark 1.3 is the newer, generally stronger default; reach for Muse Spark 1.1 when a specific cost or latency profile matters more than the latest capabilities.
Muse Spark 1.1 and Muse Spark 1.3 are both Meta models, so the real question is not which lab to trust but which tier fits your workload and budget. Muse Spark 1.1 is meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
▸Context window: 1M vs 1M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
▸Long-context recall: Muse Spark 1.3 is far stronger at 1M tokens on MRCR v2 (54.1% vs 98.1%) — important if you actually fill the window with documents.
▸Recency: Muse Spark 1.3 is the newer model by about 55 days (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Muse Spark 1.1
Muse Spark 1.3
Provider
Meta (US)
Meta (US)
Released
July 9, 2026
September 2, 2026
Context window
1M (~1,573 pages)
1M tokens (~1,500 pages)
Price (in/out)
$1.25/$4.25 per 1M tokens
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, image, video
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
54.1%
98.1%
Who wins what
Scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported)
Muse Spark 1.1
Muse Spark 1.1 lists scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported) among its strengths; Muse Spark 1.3 does not.
Subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck
Muse Spark 1.1
Muse Spark 1.1 lists subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck among its strengths; Muse Spark 1.3 does not.
Professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported)
Muse Spark 1.1
Muse Spark 1.1 lists professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported) among its strengths; Muse Spark 1.3 does not.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
Muse Spark 1.1 is comparatively weak here — not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it is the newer of the two.
Muse Spark 1.3 lists near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1) among its strengths; Muse Spark 1.1 does not.
Which should you pick?
Someone analysing very long documents or codebases
→ Muse Spark 1.1
Larger 1M window fits more in one prompt.
Anyone whose priority is scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported)
→ Muse Spark 1.1
It is specifically built for that.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
That is its strongest area.
Muse Spark 1.1: where it fits
Meta's first paid, closed-weight frontier model — class-leading agentic tool use at a quarter of rivals' price, but it trails on coding. Released July 9, 2026 by Meta, it is built for scaled tool use — 88.1 on MCP Atlas, ahead of Opus 4.8 and GPT-5.5 (vendor-reported), subagent orchestration — trained to run as a main agent or a subagent that escalates when stuck, professional agentic work — 54.7 on JobBench, a wide margin over rivals (vendor-reported), and managing its own context: it compacts the 1M window mid-run instead of relying on external windowing.
Its trade-offs are real: not the coding leader its launch framing implied — Meta's own report concedes it trails Opus 4.8 and GPT-5.5 on every coding benchmark, the 1M window oversells its recall: 54.1 on MRCR v2 at 1M against GPT-5.5's 74.0, closed weights end the free, self-hostable Llama path — this is the first model Meta has charged for, and uS-only public preview behind a waitlist, and every benchmark is vendor-reported with no third-party replication. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Because Muse Spark 1.1 and Muse Spark 1.3 come from the same lab (Meta), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. Muse Spark 1.3 is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to Muse Spark 1.3 and drop down only with a concrete reason.
Want both Muse Spark 1.1 and Muse Spark 1.3 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is Muse Spark 1.1 or Muse Spark 1.3 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Muse Spark 1.1 leans toward scaled tool use — 88.1 on mcp atlas, ahead of opus 4.8 and gpt-5.5 (vendor-reported) while Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Spark 1.1 or Muse Spark 1.3?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
Effectively neither — 1M vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from Muse Spark 1.1 to Muse Spark 1.3?
Since both are Meta models, the newer one (Muse Spark 1.3) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, Muse Spark 1.1 or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 55 days after Muse Spark 1.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.