North Mini Code vs Palmyra X6

Cohere · Canada  |  Writer · US · Updated June 2026

Quick verdict

Pick North Mini Code for agentic software engineering, code generation, and terminal tasks or efficient sparse moe — 3b active of 30b, runs on a single h100. 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 North Mini Code if you need self-hosting or data privacy; Palmyra X6 if you want a managed API.

North Mini Code (Cohere, Canada) 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. North Mini Code is cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. 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 context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecNorth Mini CodePalmyra X6
ProviderCohere (Canada) Writer (US)
ReleasedJune 9, 2026 August 13, 2026
Context window256K (~384 pages) 128K (~192 pages)
Price (in/out)Open weight (self-host / free) Not published
Open weight?Yes — self-hostable No — API only
Modalitiestext, code text, code
SWE-Bench Verified67.6% Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Agentic software engineering, code generation, and terminal tasks

North Mini Code

Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100 — and it carries the larger 256K context.

Efficient sparse MoE — 3B active of 30B, runs on a single H100

North Mini Code

Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100 — and its weights are open while Palmyra X6 is API-only.

High throughput (up to 2.8x Devstral Small 2) at low latency

North Mini Code

North Mini Code lists high throughput (up to 2.8x Devstral Small 2) at low latency among its strengths; Palmyra X6 does not.

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

Palmyra X6

North Mini Code is comparatively weak here — text-only and coding-specialized — not multimodal or general-purpose

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

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.

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; North Mini Code does not.

Largest single-prompt input

North Mini Code

Its 256K window is about 2× larger than Palmyra X6's 128K, fitting roughly 384 pages in one prompt.

Which should you pick?

Someone analysing very long documents or codebases

North Mini Code

Larger 256K window fits more in one prompt.

A team with data-privacy or self-hosting needs

North Mini Code

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

Anyone whose priority is agentic software engineering, code generation, and terminal tasks

North Mini Code

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 North Mini Code

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

North Mini Code: where it fits

Cohere's first agentic coding model: an open-weight 30B/3B-active MoE built for real software-engineering and terminal tasks that runs on a single H100. Released June 9, 2026 by Cohere, it is built for agentic software engineering, code generation, and terminal tasks, efficient sparse MoE — 3B active of 30B, runs on a single H100, high throughput (up to 2.8x Devstral Small 2) at low latency, and fully open weights under Apache 2.0 with fp8 and 4-bit builds.

Its trade-offs are real: text-only and coding-specialized — not multimodal or general-purpose, and 256K context and modest general-intelligence index trail frontier models. As an open-weight model, its running cost is your own hardware rather than a per-token fee.

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. North Mini Code 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 North Mini Code 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 North Mini Code 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, North Mini Code leans toward agentic software engineering, code generation, and terminal tasks 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, North Mini Code or Palmyra X6?

North Mini Code 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?

North Mini Code — 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 North Mini Code and Palmyra X6 together?

Yes — a multi-model platform like LumiChats gives you North Mini Code, 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, North Mini Code or Palmyra X6?

Palmyra X6 — released August 13, 2026, about 2 months after North Mini Code.

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.