MiniMax M3 vs Palmyra X6

MiniMax · China  |  Writer · US · Updated June 2026

Quick verdict

Pick MiniMax M3 for open-weight 428b moe (~23b active per token) with a 1m-token context or native multimodal input — text, image and video. 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 MiniMax M3 if you need self-hosting or data privacy; Palmyra X6 if you want a managed API.

MiniMax M3 (MiniMax, China) and Palmyra X6 (Writer, US) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. MiniMax M3 is miniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. 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

Side-by-side specs

SpecMiniMax M3Palmyra X6
ProviderMiniMax (China) Writer (US)
ReleasedMay 31, 2026 August 13, 2026
Context window1M (~1,573 pages) 128K (~192 pages)
Price (in/out)$0.23/$0.96 per 1M tokens Not published
Open weight?Yes — self-hostable No — API only
Modalitiestext, image, video, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Open-weight 428B MoE (~23B active per token) with a 1M-token context

MiniMax M3

Its 1M window holds about 8.2× more than Palmyra X6's 128K in a single prompt.

Native multimodal input — text, image and video

MiniMax M3

MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing — and it carries the larger 1M context.

Reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5

MiniMax M3

Open weights make this possible at all — Palmyra X6 is API-only, so it cannot leave the vendor's servers.

Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents

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.

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

MiniMax M3 is comparatively weak here — price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M

A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use

Palmyra X6

Palmyra X6 lists a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use among its strengths; MiniMax M3 does not.

Lowest cost at scale

Palmyra X6

Its weights are open, so at volume you pay for your own hardware instead of MiniMax M3's $0.23/$0.96 per 1M tokens.

Largest single-prompt input

MiniMax M3

Its 1M window is about 8.2× larger than Palmyra X6's 128K, fitting roughly 1,573 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

Palmyra X6

At Not published it undercuts MiniMax M3, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

MiniMax M3

Larger 1M window fits more in one prompt.

A team with data-privacy or self-hosting needs

MiniMax M3

Open weights let you run it on your own hardware; Palmyra X6 is API-only.

Anyone whose priority is open-weight 428b moe (~23b active per token) with a 1m-token context

MiniMax M3

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.

An enterprise with regional data-residency rules

Palmyra X6 or MiniMax M3

Origin (China vs US) affects where data is processed and which compliance regime applies — check the provider's terms for your region.

MiniMax M3: where it fits

MiniMax's open-weight 428B multimodal model with a 1M context — strong reported coding (59.0 SWE-Bench Pro) at low entry pricing. Released May 31, 2026 by MiniMax, it is built for open-weight 428B MoE (~23B active per token) with a 1M-token context, native multimodal input — text, image and video, reports 59.0 on SWE-Bench Pro (a strong open-weight score), surpassing GPT-5.5, and low entry pricing at $0.30/$1.20 per million up to 512K tokens.

Its trade-offs are real: price doubles to $0.60/$2.40 above 512K tokens — not flat across 1M, miniMax's own reported 80.5 SWE-Bench Verified figure is vendor-stated, not independently verified, sWE-Bench Pro is a different, harder benchmark than SWE-Bench Verified, and newer than M2.7 but with less independent testing so far. At $0.23 in / $0.96 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. MiniMax M3 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 MiniMax M3 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.

See pricing

Frequently asked questions

Is MiniMax M3 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, MiniMax M3 leans toward open-weight 428b moe (~23b active per token) with a 1m-token context 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, MiniMax M3 or Palmyra X6?

MiniMax M3 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?

MiniMax M3 — 1M vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both MiniMax M3 and Palmyra X6 together?

Yes — a multi-model platform like LumiChats gives you MiniMax M3, 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, MiniMax M3 or Palmyra X6?

Palmyra X6 — released August 13, 2026, about 2 months after MiniMax M3.

Related comparisons

Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.