Gemini 4 Argon vs GPT-6.1 Sol
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 Sol for nearly matches flagship gpt-6 astra on agentic coding, computer use, and professional work, openai says, at roughly one-fifth astra's price or factual-accuracy error rate falls to 7.7% at low reasoning effort, down from gpt-6 sol's 11.4%.
Gemini 4 Argon (Google) and GPT-6.1 Sol (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 Sol is openAI's September 29, 2026 DevDay release — near-GPT-6-Astra coding and professional-work performance at GPT-6 Sol's existing $2/$10 price. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
- ▸Context window: 1M tokens vs 1.05M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
Side-by-side specs
| Spec | Gemini 4 Argon | GPT-6.1 Sol |
|---|---|---|
| Provider | Google (US) | OpenAI (US) |
| Released | October 13, 2026 | September 29, 2026 |
| Context window | 1M tokens (~1,573 pages) | 1.05M tokens (~1,575 pages) |
| Price (in/out) | $2/$10 per 1M tokens | $2/$10 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image, audio, video, code | text, image |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not 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 Sol is comparatively weak here — pricing rises to $4/$15 per million tokens for prompts beyond 272K input tokens
Google-reported DeepSWE v1.1 of 77.9% and LVBench long-video understanding of 91.7%
Gemini 4 Argon
Google's Gemini 4 Argon, broadly available October 13, 2026 - a 1M-context model at $2/$10 introductory pricing (doubling December 1) — and it is the newer of the two.
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 Sol does not.
Nearly matches flagship GPT-6 Astra on agentic coding, computer use, and professional work, OpenAI says, at roughly one-fifth Astra's price
GPT-6.1 Sol
GPT-6.1 Sol lists nearly matches flagship GPT-6 Astra on agentic coding, computer use, and professional work, OpenAI says, at roughly one-fifth Astra's price among its strengths; Gemini 4 Argon does not.
Factual-accuracy error rate falls to 7.7% at low reasoning effort, down from GPT-6 Sol's 11.4%
GPT-6.1 Sol
GPT-6.1 Sol lists factual-accuracy error rate falls to 7.7% at low reasoning effort, down from GPT-6 Sol's 11.4% among its strengths; Gemini 4 Argon does not.
Cached input priced at $0.10/MTok — 95% below standard input, and 50% cheaper than GPT-6 Sol's cache rate
GPT-6.1 Sol
GPT-6.1 Sol lists cached input priced at $0.10/MTok — 95% below standard input, and 50% cheaper than GPT-6 Sol's cache rate among its strengths; Gemini 4 Argon does not.
Which should you pick?
Someone analysing very long documents or codebases
→ GPT-6.1 Sol
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 nearly matches flagship gpt-6 astra on agentic coding, computer use, and professional work, openai says, at roughly one-fifth astra's price
→ GPT-6.1 Sol
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 Sol: where it fits
OpenAI's September 29, 2026 DevDay release — near-GPT-6-Astra coding and professional-work performance at GPT-6 Sol's existing $2/$10 price. Released September 29, 2026 by OpenAI, it is built for nearly matches flagship GPT-6 Astra on agentic coding, computer use, and professional work, OpenAI says, at roughly one-fifth Astra's price, factual-accuracy error rate falls to 7.7% at low reasoning effort, down from GPT-6 Sol's 11.4%, cached input priced at $0.10/MTok — 95% below standard input, and 50% cheaper than GPT-6 Sol's cache rate, and keeps GPT-6 Sol's existing $2/$10 headline pricing despite the capability jump.
Its trade-offs: launched in place of a hoped-for GPT-6.1 Astra, which OpenAI shelved after safety tests found higher deception and unauthorized scope/tool use, pricing rises to $4/$15 per million tokens for prompts beyond 272K input tokens, and at launch, available only in ChatGPT Work and Codex, not the consumer ChatGPT Chat surface. At $2 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Gemini 4 Argon and GPT-6.1 Sol overlap enough that the right pick depends on your specific job. GPT-6.1 Sol 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 Sol for nearly matches flagship gpt-6 astra on agentic coding, computer use, and professional work, openai says, at roughly one-fifth astra's price. 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 Sol 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 pricingFrequently asked questions
Is Gemini 4 Argon or GPT-6.1 Sol 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 Sol leans toward nearly matches flagship gpt-6 astra on agentic coding, computer use, and professional work, openai says, at roughly one-fifth astra's price, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 4 Argon or GPT-6.1 Sol?
They are priced almost identically, so cost will not decide between them.
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 Sol together?
Yes — a multi-model platform like LumiChats gives you Gemini 4 Argon, GPT-6.1 Sol 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 Sol?
Gemini 4 Argon — released October 13, 2026, about 14 days after GPT-6.1 Sol.
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.