GPT-6.1 Sol vs Gemini 4 Argon: API price, context and cost per task
OpenAI's GPT-6.1 Sol against Google's Gemini 4 Argon. At Argon's introductory rate they land in the same price band, but they sit at different tiers: Sol is OpenAI's high-end model below the flagship, Argon is Google's flagship.
Today both list at $2 per million input tokens and $10 per million output tokens. GPT-6.1 Sol reads more per request: 1,050,000 tokens against 1,048,576.
Data updated 2026-11-11 - source: public OpenRouter model list, refreshed daily. Prices in USD, excluding VAT.
Specs and prices side by side
| GPT-6.1 Sol | Gemini 4 Argon | |
|---|---|---|
| Vendor | OpenAI | |
| Input, per 1M tokens | $2 | $2 |
| Output, per 1M tokens | $10 | $10 |
| Cached input, per 1M | $0.1 | $0.1 |
| Batch (input / output) | $1 / $5 | $1 / $5 |
| Context window | 1,050,000 | 1,048,576 |
| Max output | 128,000 | 943,718 |
| Input types | text, images, files | text, images, files, audio, video |
| Reasoning | Yes | Yes |
| Tool calling | Yes | Yes |
| On OpenRouter since | 29 Sep 2026 | 13 Oct 2026 |
Highlighted: the cheaper price or the larger limit. "Not published" means the figure is not in the public model listing yet.
What a month of work costs
Four typical workloads at today's list prices. Reasoning models also bill their thinking as output tokens, so treat output-heavy numbers as a floor.
| Workload | GPT-6.1 Sol | Gemini 4 Argon | Difference |
|---|---|---|---|
| Support chatbot10,000 conversations a month, about 1,500 input and 400 output tokens each | $70 | $70 | same |
| Coding agent300 tasks a month, about 80,000 input tokens (code context re-read across steps) and 8,000 output tokens each | $72 | $72 | same |
| Coding agent with caching70% of input served from the prompt cache | $40.08 | $40.08 | |
| Long-document analysis1,000 documents a month, about 50,000 tokens in and a 1,500-token summary out | $115 | $115 | same |
| Content drafting600 articles a month, about 3,000 tokens of brief in and 2,500 tokens of draft out | $18.60 | $18.60 | same |
Price stability over the last 30 days
- GPT-6.1 Sol: no change in the last 30 days.
- Gemini 4 Argon: no change in the last 30 days.
What the vendors and benchmarks say
GPT-6.1 Sol
"GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series."model card on OpenRouter
- Listed on OpenRouter on 29 September 2026, one week after GPT-6 Sol, which it upgrades. Source: OpenRouter
Gemini 4 Argon
"Gemini 4 Argon is Google's flagship reasoning model, built for complex software engineering, deep mathematical and scientific problem solving, and autonomous multi-step agents."model card on OpenRouter
- Announced on 30 September 2026 - Google's first new flagship generation since Gemini 3 in November 2025. Source: Google
- The output limit grew from 64,000 to 1,000,000 tokens, which Google calls the highest in the industry. Source: Google
- Introductory API rate: $2 input / $10 output per million tokens, cached input 95% cheaper. After the introductory period: $4 / $20. Source: Google
- Google-reported results: DeepSWE v1.1 77.9%, AutomationBench 51.3% (1st), LVBench 91.7%. Text Arena 1525 (1st), but Code Arena WebDev 1679 (8th). Source: Google; arena rankings
- Staged access: trusted testers first, then paying API customers and Google AI Ultra subscribers. Not in the public API as of 30 September 2026. Source: Google
Which one to pick
If Argon's launch numbers hold, it offers flagship results for a mid-tier price - but only during the introductory period, after which Google's announced rate doubles. Sol is in the public API today and is the safer production choice; Argon is worth testing as soon as you get access.
Cheaper models with a similar context window
Models from our comparison set that cost less than both on a blended basis and support tool calling. They are not equivalent in quality - test before switching.
- Qwen3.8 Max (Alibaba (Qwen)): $2 / $6 per million tokens, 1M context
- Gemini 3.8 Flash (Google): $0.825 / $4.13 per million tokens, 1.05M context
- DeepSeek V4 Pro (DeepSeek): $0.955 / $1.91 per million tokens, 1.05M context
Related reading
How we calculate
Prices are the public per-token list rates from OpenRouter's model list, which match the vendors' own API prices for first-party models and show the current routed price for open-weight models served by several hosts. Monthly costs multiply those rates by the token volumes in each workload; caching assumes the stated share of input is billed at the cached-input rate. Benchmarks and claims are quoted from the named sources, mostly the vendors themselves - treat them as a guide and test on your own tasks. See also the AI cost calculator and all tracked model prices.
Frequently asked questions
Which is cheaper, GPT-6.1 Sol or Gemini 4 Argon?
As of 11 Nov 2026, GPT-6.1 Sol costs $2 per million input tokens and $10 per million output tokens; Gemini 4 Argon costs $2 and $10. GPT-6.1 Sol is cheaper in 0 of the 4 monthly workloads we price on this page. The real bill also depends on how many reasoning tokens each model writes.
Which has the larger context window?
GPT-6.1 Sol reads up to 1,050,000 tokens and can write up to 128,000; Gemini 4 Argon reads up to 1,048,576 and writes up to 943,718.
How much does a support chatbot cost on each model?
For 10,000 conversations a month (about 15 million input and 4 million output tokens) you would pay about $70 on GPT-6.1 Sol and $70 on Gemini 4 Argon at list prices, before any caching or batch discounts.
Do they offer prompt caching or batch discounts?
GPT-6.1 Sol lists cached input at $0.1 per million and a batch rate of $1 / $5. Gemini 4 Argon lists cached input at $0.1 per million and a batch rate of $1 / $5. Caching matters most for agents and chatbots that resend the same context on every turn.
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