GPT-6.1 Terra vs Palmyra X6

OpenAI · US  |  Writer · US · Updated June 2026

Quick verdict

Pick GPT-6.1 Terra for $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra or terminal-bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for gpt-5.6 terra (openai-reported). 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.

GPT-6.1 Terra (OpenAI) and Palmyra X6 (Writer) are two of the models people most often weigh against each other in 2026. GPT-6.1 Terra is openAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor. 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

Side-by-side specs

SpecGPT-6.1 TerraPalmyra X6
ProviderOpenAI (US) Writer (US)
ReleasedOctober 26, 2026 August 13, 2026
Context window1.05M tokens (~1,575 pages) 128K (~192 pages)
Price (in/out)$1/$5 per 1M tokens Not published
Open weight?No — API only No — API only
Modalitiestext, image, code text, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

$1/$5 per million tokens (cached input $0.05) - half the price of GPT-6.1 Sol and GPT-5.6 Terra

GPT-6.1 Terra

Its 1.05M tokens window holds about 8.2× more than Palmyra X6's 128K in a single prompt.

Terminal-Bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for GPT-5.6 Terra (OpenAI-reported)

GPT-6.1 Terra

Palmyra X6 is comparatively weak here — not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis

1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API

GPT-6.1 Terra

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

Palmyra X6 lists enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents among its strengths; GPT-6.1 Terra 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

GPT-6.1 Terra is comparatively weak here — requests above 272K input tokens are billed at 2x input and 1.5x output for the whole request

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

Palmyra X6

GPT-6.1 Terra is comparatively weak here — closed weights and no fine-tuning support

Lowest cost at scale

Palmyra X6

Its weights are open, so at volume you pay for your own hardware instead of GPT-6.1 Terra's $1/$5 per 1M tokens.

Largest single-prompt input

GPT-6.1 Terra

Its 1.05M tokens window is about 8.2× larger than Palmyra X6's 128K, fitting roughly 1,575 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ Palmyra X6

At Not published it undercuts GPT-6.1 Terra, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ GPT-6.1 Terra

Larger 1.05M tokens window fits more in one prompt.

Anyone whose priority is $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra

→ GPT-6.1 Terra

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.

GPT-6.1 Terra: where it fits

OpenAI's October 26, 2026 mid-tier model - a 1.05M-context, computer-use-capable GPT at $1/$5 per million tokens, half the price of its predecessor. Released October 26, 2026 by OpenAI, it is built for $1/$5 per million tokens (cached input $0.05) - half the price of GPT-6.1 Sol and GPT-5.6 Terra, terminal-Bench 4.0 of 50.3% at maximum reasoning effort, versus 21.5% for GPT-5.6 Terra (OpenAI-reported), 1.05M-token context with up to 128K output tokens, plus image input and computer use via the Responses API, and error rate on OpenAI's hard-prompt set falls from 53.6% (GPT-5.6 Terra) to 16.7% at low effort and 4.3% at max effort.

Its trade-offs are real: openAI still positions Sol and Astra as the higher-capability choices for demanding coding problems, requests above 272K input tokens are billed at 2x input and 1.5x output for the whole request, closed weights and no fine-tuning support, and benchmark figures are vendor-reported; no SWE-bench Verified or MRCR numbers published. At $1 in / $5 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

GPT-6.1 Terra and Palmyra X6 overlap enough that the right pick depends on your specific job. Palmyra X6 costs less per token; GPT-6.1 Terra holds the larger context; and each leads in its own area — GPT-6.1 Terra for $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra, 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 GPT-6.1 Terra 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 GPT-6.1 Terra 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, GPT-6.1 Terra leans toward $1/$5 per million tokens (cached input $0.05) - half the price of gpt-6.1 sol and gpt-5.6 terra 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, GPT-6.1 Terra or Palmyra X6?

Palmyra X6 is cheaper — $1/$5 per 1M tokens vs Not published.

Which has the bigger context window?

GPT-6.1 Terra — 1.05M tokens 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 GPT-6.1 Terra and Palmyra X6 together?

Yes — a multi-model platform like LumiChats gives you GPT-6.1 Terra, 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, GPT-6.1 Terra or Palmyra X6?

GPT-6.1 Terra — released October 26, 2026, about 2 months after Palmyra X6.

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.