Gemini 4 Argon vs GPT-6.1 Terra

Google · US  |  OpenAI · US · Updated June 2026

Quick verdict

Pick Gemini 4 Argon for 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses or google-reported deepswe v1.1 of 77.9% and lvbench long-video understanding of 91.7%. 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). On a tight budget at scale, GPT-6.1 Terra is the value pick.

Gemini 4 Argon (Google) and GPT-6.1 Terra (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 4 Argon is google's Gemini 4 Argon, broadly available October 13, 2026 - a 1M-context model at $2/$10 introductory pricing (doubling December 1). 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. 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

SpecGemini 4 ArgonGPT-6.1 Terra
ProviderGoogle (US) OpenAI (US)
ReleasedOctober 13, 2026 October 26, 2026
Context window1M tokens (~1,573 pages) 1.05M tokens (~1,575 pages)
Price (in/out)$2/$10 per 1M tokens $1/$5 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image, audio, video, code text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses

Gemini 4 Argon

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

Google-reported DeepSWE v1.1 of 77.9% and LVBench long-video understanding of 91.7%

Gemini 4 Argon

GPT-6.1 Terra is comparatively weak here — benchmark figures are vendor-reported; no SWE-bench Verified or MRCR numbers published

Artificial Analysis Intelligence Index of 53 at high effort (AI Weekly)

Gemini 4 Argon

Gemini 4 Argon lists artificial Analysis Intelligence Index of 53 at high effort (AI Weekly) among its strengths; GPT-6.1 Terra does not.

$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

At $1/$5 per 1M tokens it undercuts Gemini 4 Argon ($2/$10 per 1M tokens), and that gap compounds at volume.

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

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 — and it runs cheaper at $1/$5 per 1M tokens.

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

GPT-6.1 Terra

Gemini 4 Argon is comparatively weak here — verbose: about 62K output tokens per Artificial Analysis task, so cost per task is high

Lowest cost at scale

GPT-6.1 Terra

At $1/$5 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.

Which should you pick?

A cost-sensitive startup shipping high volume

→ GPT-6.1 Terra

At $1/$5 per 1M tokens it undercuts Gemini 4 Argon, 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 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses

→ Gemini 4 Argon

It is specifically built for that.

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

That is its strongest area.

Gemini 4 Argon: where it fits

Google's Gemini 4 Argon, broadly available October 13, 2026 - a 1M-context model at $2/$10 introductory pricing (doubling December 1). Released October 13, 2026 by Google, it is built for 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses, google-reported DeepSWE v1.1 of 77.9% and LVBench long-video understanding of 91.7%, and artificial Analysis Intelligence Index of 53 at high effort (AI Weekly).

Its trade-offs are real: introductory $2/$10 pricing ends November 30; from December 1 it doubles to $4/$20, verbose: about 62K output tokens per Artificial Analysis task, so cost per task is high, and announced September 30 for trusted cyber defenders only; broad paid-tier availability followed October 13 (not on the free tier). At $2 in / $10 out per million tokens, it sits in the mid price band.

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: 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.

The bottom line for this matchup

Gemini 4 Argon and GPT-6.1 Terra overlap enough that the right pick depends on your specific job. GPT-6.1 Terra costs less per token; GPT-6.1 Terra holds the larger context; and each leads in its own area — Gemini 4 Argon for 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses, 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. Rather than crowning one, run the same hard task through both once and let the results decide.

Want both Gemini 4 Argon and GPT-6.1 Terra 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 Gemini 4 Argon or GPT-6.1 Terra 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, Gemini 4 Argon leans toward 1,048,576-token unified context shared by input, thinking and output, with 'long decode' for very long responses while 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, and that positioning usually predicts which feels better on your codebase.

Which is cheaper, Gemini 4 Argon or GPT-6.1 Terra?

GPT-6.1 Terra is cheaper — $2/$10 per 1M tokens vs $1/$5 per 1M tokens, roughly 2× apart on input.

Which has the bigger context window?

Effectively neither — 1M tokens vs 1.05M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Gemini 4 Argon and GPT-6.1 Terra together?

Yes — a multi-model platform like LumiChats gives you Gemini 4 Argon, GPT-6.1 Terra 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, Gemini 4 Argon or GPT-6.1 Terra?

GPT-6.1 Terra — released October 26, 2026, about 13 days after Gemini 4 Argon.

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.