Is Gemini 4 Argon cheaper than Gemini 3.1 Pro?

Yes, on current list prices. Both charge $2 per million input tokens, but Argon's $10/M output rate undercuts Pro's $12/M, making Argon cheaper for any workload that generates output tokens. The gap widens as output volume grows relative to input.

Will Gemini 4 Argon stay this cheap?

Not necessarily. Argon's $2/$10 pricing is described as an introductory rate, with reports indicating it's set to double to roughly $4/$20 per million tokens around December 1, 2026. Confirm current pricing before locking in long-term cost projections.

Does context window size affect pricing for these models?

For Gemini 3.1 Pro, yes — pricing is tiered, with higher rates applying to prompts exceeding roughly 200,000 tokens. Gemini 4 Argon reportedly applies one flat rate across its full context window, with no separate long-context pricing tier.

Which model is better for output-heavy tasks like long reports or reasoning chains?

Gemini 4 Argon is the more cost-efficient choice for output-heavy tasks today, since its $10/M output price is lower than Gemini 3.1 Pro's $12/M. The savings scale directly with how many output tokens your workload produces each month.

HEAD-TO-HEAD · FLAGSHIP-TIER · VERIFIED OCTOBER 15, 2026

Gemini 4 Argon vs Gemini 3.1 Pro — which is actually cheaper?

Both models share the same $2/M input price, so the entire cost gap comes down to output tokens: Gemini 4 Argon charges $10/M versus Gemini 3.1 Pro's $12/M. For output-heavy workloads like long-form generation or reasoning traces, that $2 difference compounds fast at scale.

Spec	Gemini 4 Argon	Gemini 3.1 Pro
Input / 1M tokens	$2.00	$2.00
Output / 1M tokens	$10.00	$12.00
Context window	1M	2M (1M/200K tiered pricing split)

The output price gap

The headline difference between these two models is output pricing. Gemini 4 Argon bills output at $10 per million tokens, while Gemini 3.1 Pro bills at $12 per million — a 16.7% premium for Pro. Since input pricing is identical at $2/M for both, every dollar of cost difference in a typical request traces back to how many output tokens you generate. Workloads that lean heavily on long completions, chain-of-thought reasoning, or verbose responses will see the gap widen proportionally, making Argon the more economical choice on raw per-token output cost today.

Context window

Gemini 4 Argon ships with a unified 1M-token context window covering both input and output. Gemini 3.1 Pro is generally understood to support up to a 2M-token context window, though its pricing is tiered: the $2/$12 rate we're comparing applies only to prompts up to 200,000 tokens, after which Google's published rate steps up to $4/$18. Treat the context-window figures as approximate — Argon's limit is well-documented at launch, but Pro's long-context ceiling and tiered pricing are worth double-checking against Google's live docs before budgeting for very large prompts.

Worked example

At 100M input tokens and 30M output tokens per month: Gemini 4 Argon costs (100 × $2) + (30 × $10) = $200 + $300 = $500/month. Gemini 3.1 Pro costs (100 × $2) + (30 × $12) = $200 + $360 = $560/month (assuming prompts stay under the 200K-token tier). That's a $60/month (about 10.7%) savings with Argon at this volume, growing larger as output token share increases.

Prices from the LLM Price Watch daily tracker, 2026-10-15. Prices change; use the calculator with your own usage for an exact comparison, or see the full price table for every tracked model.