Pick Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. 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). Choose Laguna XS 2.1 if you need self-hosting or data privacy; Palmyra X6 if you want a managed API.
Laguna XS 2.1 (Poolside) and Palmyra X6 (Writer) are two of the models people most often weigh against each other in 2026. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences
Cost model: Laguna XS 2.1 ships open weights you can self-host (hardware cost only, no per-token fee), while Palmyra X6 is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
Context window: Laguna XS 2.1 holds 2× more — 256K (~393 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: Palmyra X6 is the newer model by about 42 days (released August 13, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Laguna XS 2.1
Palmyra X6
Provider
Poolside (US)
Writer (US)
Released
July 2, 2026
August 13, 2026
Context window
256K (~393 pages)
128K (~192 pages)
Price (in/out)
$0.1/$0.2 per 1M tokens
Not published
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, code
SWE-Bench Verified
70.9%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters: Laguna XS 2.1 — Palmyra X6 is comparatively weak here — not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime: Laguna XS 2.1 — Open weights make this possible at all — Palmyra X6 is API-only, so it cannot leave the vendor's servers.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price: Laguna XS 2.1 — Palmyra X6 is comparatively weak here — no public per-token API price - sold through Writer's enterprise platform, not a self-serve API
Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents: Palmyra X6 — Laguna XS 2.1 is comparatively weak here — weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise
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 — Laguna XS 2.1 is comparatively weak here — weeks old with no independent replication; every published score traces back to Poolside's own harness
A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use: Palmyra X6 — Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half — and it is the newer of the two.
Lowest cost at scale: Palmyra X6 — Its weights are open, so at volume you pay for your own hardware instead of Laguna XS 2.1's $0.1/$0.2 per 1M tokens.
Largest single-prompt input: Laguna XS 2.1 — Its 256K window is about 2× larger than Palmyra X6's 128K, fitting roughly 393 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Palmyra X6 — At Not published it undercuts Laguna XS 2.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Laguna XS 2.1 — Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs: Laguna XS 2.1 — Open weights let you run it on your own hardware; Palmyra X6 is API-only.
Anyone whose priority is remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters: Laguna XS 2.1 — 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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs are real: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 out per million tokens, it sits in the budget 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
The defining split here is open vs. closed. Laguna XS 2.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Palmyra X6 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Frequently asked questions
Is Laguna XS 2.1 or Palmyra X6 better for coding?
Public SWE-Bench figures are not available for Palmyra X6, so the honest test is your own repository — run an identical real bug through both. By design, Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters 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, Laguna XS 2.1 or Palmyra X6?
Laguna XS 2.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Palmyra X6 is API-metered at Not published. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Laguna XS 2.1 — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Laguna XS 2.1 and Palmyra X6 together?
Yes — a multi-model platform like LumiChats gives you Laguna XS 2.1, 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, Laguna XS 2.1 or Palmyra X6?
Palmyra X6 — released August 13, 2026, about 42 days after Laguna XS 2.1.
Laguna XS 2.1 vs Palmyra X6
Poolside · US | Writer · US · Updated June 2026
Quick verdict
Pick Laguna XS 2.1 for remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters or open weights under openmdw-1.1, shipped day one in bf16, fp8, nvfp4 and int4 across every major runtime. 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). Choose Laguna XS 2.1 if you need self-hosting or data privacy; Palmyra X6 if you want a managed API.
Laguna XS 2.1 (Poolside) and Palmyra X6 (Writer) are two of the models people most often weigh against each other in 2026. Laguna XS 2.1 is a 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. 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, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
▸Cost model: Laguna XS 2.1 ships open weights you can self-host (hardware cost only, no per-token fee), while Palmyra X6 is API-metered at Not published. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
▸Context window: Laguna XS 2.1 holds 2× more — 256K (~393 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: Palmyra X6 is the newer model by about 42 days (released August 13, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Laguna XS 2.1
Palmyra X6
Provider
Poolside (US)
Writer (US)
Released
July 2, 2026
August 13, 2026
Context window
256K (~393 pages)
128K (~192 pages)
Price (in/out)
$0.1/$0.2 per 1M tokens
Not published
Open weight?
Yes — self-hostable
No — API only
Modalities
text, code
text, code
SWE-Bench Verified
70.9%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters
Laguna XS 2.1
Palmyra X6 is comparatively weak here — not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis
Open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime
Laguna XS 2.1
Open weights make this possible at all — Palmyra X6 is API-only, so it cannot leave the vendor's servers.
Cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price
Laguna XS 2.1
Palmyra X6 is comparatively weak here — no public per-token API price - sold through Writer's enterprise platform, not a self-serve API
Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents
Palmyra X6
Laguna XS 2.1 is comparatively weak here — weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise
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
Laguna XS 2.1 is comparatively weak here — weeks old with no independent replication; every published score traces back to Poolside's own harness
A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use
Palmyra X6
Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half — and it is the newer of the two.
Lowest cost at scale
Palmyra X6
Its weights are open, so at volume you pay for your own hardware instead of Laguna XS 2.1's $0.1/$0.2 per 1M tokens.
Largest single-prompt input
Laguna XS 2.1
Its 256K window is about 2× larger than Palmyra X6's 128K, fitting roughly 393 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Palmyra X6
At Not published it undercuts Laguna XS 2.1, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Laguna XS 2.1
Larger 256K window fits more in one prompt.
A team with data-privacy or self-hosting needs
→ Laguna XS 2.1
Open weights let you run it on your own hardware; Palmyra X6 is API-only.
Anyone whose priority is remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters
→ Laguna XS 2.1
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.
Laguna XS 2.1: where it fits
A 33B open-weight coding MoE running on 3B active parameters — 70.9% SWE-Bench Verified and very cheap, but unproven. Released July 2, 2026 by Poolside, it is built for remarkable efficiency — 70.9% on SWE-Bench Verified from only 3B active parameters, open weights under OpenMDW-1.1, shipped day one in BF16, FP8, NVFP4 and INT4 across every major runtime, cheap even on the paid tier, at roughly a sixth of GLM 4.7's input price, and unusually transparent evaluation — it publishes its harness, step limits, and sandbox specs.
Its trade-offs are real: weeks old with no independent replication; every published score traces back to Poolside's own harness, the free endpoint trains on your inputs and outputs — disqualifying for proprietary code, which is its main use case, and weak on harder agentic work (37.5 on Terminal-Bench 2.0), and its gain over XS.2 is barely above noise. At $0.1 in / $0.2 out per million tokens, it sits in the budget 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
The defining split here is open vs. closed. Laguna XS 2.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Palmyra X6 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Laguna XS 2.1 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.
Public SWE-Bench figures are not available for Palmyra X6, so the honest test is your own repository — run an identical real bug through both. By design, Laguna XS 2.1 leans toward remarkable efficiency — 70.9% on swe-bench verified from only 3b active parameters 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, Laguna XS 2.1 or Palmyra X6?
Laguna XS 2.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Palmyra X6 is API-metered at Not published. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Laguna XS 2.1 — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Laguna XS 2.1 and Palmyra X6 together?
Yes — a multi-model platform like LumiChats gives you Laguna XS 2.1, 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, Laguna XS 2.1 or Palmyra X6?
Palmyra X6 — released August 13, 2026, about 42 days after Laguna XS 2.1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.