Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). Pick Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents or writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (writer's own figures). On a tight budget at scale, Palmyra X6 is the value pick.
Muse Spark 1.3 (Meta) and Palmyra X6 (Writer) are two of the models people most often weigh against each other in 2026. 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. Palmyra X6 is writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Muse Spark 1.3 holds 7.8× more — 1M tokens (~1,500 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Muse Spark 1.3 is the newer model by about 20 days (released September 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Muse Spark 1.3
Palmyra X6
Provider
Meta (US)
Writer (US)
Released
September 2, 2026
August 13, 2026
Context window
1M tokens (~1,500 pages)
128K (~192 pages)
Price (in/out)
$1.25/$4.25 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, video
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
98.1%
Not published
Who wins what
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2: Muse Spark 1.3 — Its 1M tokens window holds about 7.8× more than Palmyra X6's 128K in a single prompt.
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 carries the larger 1M tokens context.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1): 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.
Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents: Palmyra X6 — Palmyra X6 lists enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents among its strengths; Muse Spark 1.3 does not.
Writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures): Palmyra X6 — Palmyra X6 lists writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures) among its strengths; Muse Spark 1.3 does not.
A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use: Palmyra X6 — Muse Spark 1.3 is comparatively weak here — not yet open-weight, despite Meta roadmapping a future Muse Spark weights release
Lowest cost at scale: Palmyra X6 — Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Largest single-prompt input: Muse Spark 1.3 — Its 1M tokens window is about 7.8× larger than Palmyra X6's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Palmyra X6 — At Not published it undercuts Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Muse Spark 1.3 — Larger 1M tokens window fits more in one prompt.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2: Muse Spark 1.3 — It is specifically built for that.
Anyone whose priority is enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents: Palmyra X6 — That is its strongest area.
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 are real: 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.
Palmyra X6: where it fits
Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. Released August 13, 2026 by Writer, it is built for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures), and a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use.
Its trade-offs: no public per-token API price - sold through Writer's enterprise platform, not a self-serve API, not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis, and built for a narrower enterprise-agent use case rather than general-purpose chat.
The bottom line for this matchup
Muse Spark 1.3 and Palmyra X6 overlap enough that the right pick depends on your specific job. Palmyra X6 costs less per token; Muse Spark 1.3 holds the larger context; and each leads in its own area — Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Muse Spark 1.3 or Palmyra X6 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 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 while Palmyra X6 leans toward enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Spark 1.3 or Palmyra X6?
Palmyra X6 is cheaper — $1.25/$4.25 per 1M tokens vs Not published.
Which has the bigger context window?
Muse Spark 1.3 — 1M tokens vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Muse Spark 1.3 and Palmyra X6 together?
Yes — a multi-model platform like LumiChats gives you Muse Spark 1.3, Palmyra X6 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Muse Spark 1.3 or Palmyra X6?
Muse Spark 1.3 — released September 2, 2026, about 20 days after Palmyra X6.
Muse Spark 1.3 vs Palmyra X6
Meta · US | Writer · US · Updated June 2026
Quick verdict
Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). Pick Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents or writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (writer's own figures). On a tight budget at scale, Palmyra X6 is the value pick.
Muse Spark 1.3 (Meta) and Palmyra X6 (Writer) are two of the models people most often weigh against each other in 2026. 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. Palmyra X6 is writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Muse Spark 1.3 holds 7.8× more — 1M tokens (~1,500 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Muse Spark 1.3 is the newer model by about 20 days (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Muse Spark 1.3
Palmyra X6
Provider
Meta (US)
Writer (US)
Released
September 2, 2026
August 13, 2026
Context window
1M tokens (~1,500 pages)
128K (~192 pages)
Price (in/out)
$1.25/$4.25 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, video
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
98.1%
Not published
Who wins what
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
Its 1M tokens window holds about 7.8× more than Palmyra X6's 128K in a single prompt.
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 carries the larger 1M tokens context.
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.
Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents
Palmyra X6
Palmyra X6 lists enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents among its strengths; Muse Spark 1.3 does not.
Writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures)
Palmyra X6
Palmyra X6 lists writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures) among its strengths; Muse Spark 1.3 does not.
A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use
Palmyra X6
Muse Spark 1.3 is comparatively weak here — not yet open-weight, despite Meta roadmapping a future Muse Spark weights release
Lowest cost at scale
Palmyra X6
Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Largest single-prompt input
Muse Spark 1.3
Its 1M tokens window is about 7.8× larger than Palmyra X6's 128K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Palmyra X6
At Not published it undercuts Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark 1.3
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
It is specifically built for that.
Anyone whose priority is enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents
→ Palmyra X6
That is its strongest area.
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 are real: 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.
Palmyra X6: where it fits
Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. Released August 13, 2026 by Writer, it is built for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures), and a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use.
Its trade-offs: no public per-token API price - sold through Writer's enterprise platform, not a self-serve API, not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis, and built for a narrower enterprise-agent use case rather than general-purpose chat.
The bottom line for this matchup
Muse Spark 1.3 and Palmyra X6 overlap enough that the right pick depends on your specific job. Palmyra X6 costs less per token; Muse Spark 1.3 holds the larger context; and each leads in its own area — Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Muse Spark 1.3 and Palmyra X6 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 1.3 or Palmyra X6 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 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 while Palmyra X6 leans toward enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Muse Spark 1.3 or Palmyra X6?
Palmyra X6 is cheaper — $1.25/$4.25 per 1M tokens vs Not published.
Which has the bigger context window?
Muse Spark 1.3 — 1M tokens vs 128K, about 7.8× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Muse Spark 1.3 and Palmyra X6 together?
Yes — a multi-model platform like LumiChats gives you Muse Spark 1.3, Palmyra X6 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Muse Spark 1.3 or Palmyra X6?
Muse Spark 1.3 — released September 2, 2026, about 20 days after Palmyra X6.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.