Model comparison

Gemini 3.7 Flash vs GPT-5.6 Sol

Google against OpenAI, compared on context, price, and attributed benchmark results.

Recorded profile verification October 1, 2026Individual provider fields may changeEvidence confidence: Medium — see receipts below

Google

Gemini 3.7 Flash

Budget

OpenAI

GPT-5.6 Sol

Frontier

AI model capability comparison
Specification	Gemini 3.7 Flash	GPT-5.6 Sol
Provider
Provider	Google	OpenAI
Tier
Tier	Budget	Frontier
Context window
Context window	1.05M	Winner: 1.05M
Max output
Max output	66K	Winner: 128K
Input / 1M tokens
Input / 1M tokens	Winner: $0.75	$4
Output / 1M tokens
Output / 1M tokens	Winner: $3.75	$20
Weights
Weights	Closed	Closed
Parameters
Parameters	Not verifiedUnverified	Not verifiedUnverified
Reasoning levels
Reasoning levels	low, medium, high	none, low, medium, high, xhigh, max
Modalities
Modalities	text, image, video, audio, pdf	text, image
API model id
API model id	gemini-3.7-flash	gpt-5.6-sol
Released
Released	August 13, 2026	July 9, 2026
Terminal-Bench 2.1 · source date Gemini 3.7 Flash: 2026-08, GPT-5.6 Sol: 2026-07-09 (comparability not verified)
Terminal-Bench 2.1 · source date Gemini 3.7 Flash: 2026-08, GPT-5.6 Sol: 2026-07-09 (comparability not verified)	85.8	88.8
DeepSWE 1.1 · source date Gemini 3.7 Flash: 2026-08
DeepSWE 1.1 · source date Gemini 3.7 Flash: 2026-08	65.3	Not verifiedUnverified
HLE-Verified · source date Gemini 3.7 Flash: 2026-08
HLE-Verified · source date Gemini 3.7 Flash: 2026-08	53.6	Not verifiedUnverified
GPQA Diamond · source date GPT-5.6 Sol: 2026-07-09
GPQA Diamond · source date GPT-5.6 Sol: 2026-07-09	Not verifiedUnverified	94.6

Dates beside benchmark scores refer to the linked source’s publication or capture date unless that source explicitly states when it measured the result. A shared URL alone does not establish comparable runs; unverified setups are marked. Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.

Benchmark receipts

Where each score comes from, and how far it can be compared across models.

Source date2026-08
Google DeepMind model evaluation report (vendor; full 1,811-item HLE-Verified set) (Full 1,811-item verified/revised set; differs from original HLE and AA text-only HLE)
Expert reasoning on the verified and revised Humanity's Last Exam question set.
UnknownA distinct question set from original HLE and Artificial Analysis's text-only HLE. Shared dataset and publisher alone do not establish matching model effort, tools, filtering and run configuration; no quality winner is inferred without that evidence.
Source date2026-08
Google DeepMind model evaluation report (vendor, mini-swe-agent, high thinking)
Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task.
Directly comparable
Source date2026-08
Google DeepMind model evaluation report (vendor, Terminus 2 harness)
Agentic terminal work: multi-step tasks executed in a sandboxed shell environment.
Comparable with caveatNot comparable with Terminal-Bench 3.0 or 4.0 (different task sets) or v1; harness configuration (container, time limits) also shifts results.
Source date2026-07-09
OpenAI — GPT-5.6 evals table (vendor)
Graduate-level science reasoning: multiple-choice questions written by domain PhDs.
Comparable with caveatDo not treat a fixed two-point band as universal measurement uncertainty; it depends on run count and evaluation setup. Chain-of-thought, prompt, and tool policy must match. The small pool limits fine-grained conclusions, and frontier scores can be near ceiling; Artificial Analysis dropped it from its Intelligence Index in v4.3.
Source date2026-07-09
OpenAI — GPT-5.6 evals table (vendor; Ultra multi-agent config: 91.9)
Agentic terminal work: multi-step tasks executed in a sandboxed shell environment.
Comparable with caveatNot comparable with Terminal-Bench 3.0 or 4.0 (different task sets) or v1; harness configuration (container, time limits) also shifts results.

Pricing tiers

Gemini 3.7 Flash: Intro Standard $0.75/$3.75 per MTok through December 31, 2026; $1.50/$7.50 from January 1, 2027. Output includes thinking tokens. Cached input $0.075, rising to $0.15; storage $0.50/MTok-hour, rising to $1. Batch/Flex input/output are $0.375/$1.875, rising to $0.75/$3.75. Priority $1.35/$6.75, rising to $2.70/$13.50. Grounding tools have separate charges and quotas; free-tier limits differ from paid.

GPT-5.6 Sol: Launch $5/$30, reduced to promotional $4/$20 on August 21; available at least through November 21, 2026. Above 272K input the full request bills $8/$30. Cached input $0.40/$0.80 short/long and cache writes $5/$10. Batch is $2/$10 at short context. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff Feb 16 2026.

BudgetRecord checked October 1, 2026

Gemini 3.7 Flash

Google describes Gemini 3.7 Flash as its efficient multimodal option for everyday coding and agentic tool use; the newer 3.8 is offered for more demanding workflows.

Best for

High-volume multimodal
Agent loops
Cost-sensitive work

Watch out

Intro rates and cache storage double January 1, 2027. Minimal thinking errors; computer use is Preview. Measure accepted-task costs and token use before switching to the newer 3.8 rather than assuming uniform savings or quality.

FrontierRecord checked October 1, 2026

GPT-5.6 Sol

GPT-5.6 Sol was OpenAI's GPT-5.6 flagship for complex reasoning and coding with a 1.05M-token context — superseded on 2026-09-22 by GPT-6 Sol at half the price.

Best for

Complex reasoning
Agentic coding
Hard knowledge work

Watch out

GPT-6.1 Sol is the newer Sol option at $2/$10 Standard. GPT-5.6 Sol remains listed; its $4/$20 price is promotional. Max effort can increase token use, and Ultra is a multi-agent configuration rather than a separate reasoning.effort value.

When the cheaper one wins

Gemini 3.7 Flash is cheaper on output at $3.75 per million tokens against $20 for GPT-5.6 Sol — about 5.3×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. On DeepSWE 1.1, Gemini 3.7 Flash is 65.5% Pass@1 at $2.03/task versus GPT-5.6 Sol at 72.7% / $8.39/task. This compares standard short-context token rates, not total cost per accepted task. Include input, cache, context tiers, schedules, retries and review in your pilot.

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Evidence confidence: Medium

How strong and complete the evidence behind this comparison is — not a prediction of which model is better.

Pricing verified on both sides — Input and output rates are verified for both models.
4/5 core specs verified on both sides — Not published for at least one side: parameter count.
No directly aligned benchmark setup — No benchmark has matching cited sources, source dates, units, effort and recorded run details on both models.
Verified within the last 90 days — Older of the two catalog checks was 25 days ago.
Both models carry source citations — Each side has at least two catalog sources on record.

Source receipts

Each catalog figure was checked against the provider or an independent second source on the date shown.

Gemini 3.7 Flash: Google primary profile — whole-record source check October 1 (accessed 2026-10-01)
Gemini 3.7 Flash: Gemini current API pricing and cache-storage tiers (accessed 2026-10-01)
Gemini 3.7 Flash: Google — Gemini 3.7 Flash (accessed 2026-08-29)
Gemini 3.7 Flash: Google Cloud Gemini pricing (accessed 2026-08-29)
GPT-5.6 Sol: OpenAI model card — whole-profile source check October 1 (accessed 2026-10-01)
GPT-5.6 Sol: OpenAI current API pricing and processing tiers (accessed 2026-10-01)
GPT-5.6 Sol: OpenAI — GPT-5.6 (accessed 2026-08-29)
GPT-5.6 Sol: OpenAI API pricing (gpt-5.6-sol $4/$20) (accessed 2026-08-29)
GPT-5.6 Sol: OpenAI — Introducing GPT-6 Sol and Luna (GPT-5.6 Sol successor) (accessed 2026-09-26)

Related comparisons

Diving deeper on one model? Gemini 3.7 Flash · GPT-5.6 Sol

Common questions

Gemini 3.7 Flash vs GPT-5.6 Sol

Answered from the verified figures on this page rather than general guidance.

Is Gemini 3.7 Flash or GPT-5.6 Sol cheaper for input?

Gemini 3.7 Flash is cheaper at $0.75 per million input tokens, against $4 for GPT-5.6 Sol — roughly 5.3× the price. Estimate both input and output token volume for your workload. These are base rates; Gemini 3.7 Flash: Intro Standard $0.75/$3.75 per MTok through December 31, 2026; $1.50/$7.50 from January 1, 2027. Output includes thinking tokens. Cached input $0.075, rising to $0.15; storage $0.50/MTok-hour, rising to $1. Batch/Flex input/output are $0.375/$1.875, rising to $0.75/$3.75. Priority $1.35/$6.75, rising to $2.70/$13.50. Grounding tools have separate charges and quotas; free-tier limits differ from paid. GPT-5.6 Sol: Launch $5/$30, reduced to promotional $4/$20 on August 21; available at least through November 21, 2026. Above 272K input the full request bills $8/$30. Cached input $0.40/$0.80 short/long and cache writes $5/$10. Batch is $2/$10 at short context. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff Feb 16 2026.

Is Gemini 3.7 Flash or GPT-5.6 Sol cheaper for output?

Gemini 3.7 Flash is cheaper at $3.75 per million output tokens, against $20 for GPT-5.6 Sol — roughly 5.3× the price. Estimate both input and output token volume for your workload. These are base rates; Gemini 3.7 Flash: Intro Standard $0.75/$3.75 per MTok through December 31, 2026; $1.50/$7.50 from January 1, 2027. Output includes thinking tokens. Cached input $0.075, rising to $0.15; storage $0.50/MTok-hour, rising to $1. Batch/Flex input/output are $0.375/$1.875, rising to $0.75/$3.75. Priority $1.35/$6.75, rising to $2.70/$13.50. Grounding tools have separate charges and quotas; free-tier limits differ from paid. GPT-5.6 Sol: Launch $5/$30, reduced to promotional $4/$20 on August 21; available at least through November 21, 2026. Above 272K input the full request bills $8/$30. Cached input $0.40/$0.80 short/long and cache writes $5/$10. Batch is $2/$10 at short context. Regional/FedRAMP processing adds 10% where eligible. Knowledge cutoff Feb 16 2026.

Which has the larger context window, Gemini 3.7 Flash or GPT-5.6 Sol?

Both accept about 1.05M tokens of context, so document length will not decide between them.

Do Gemini 3.7 Flash and GPT-5.6 Sol support the same reasoning levels?

Gemini 3.7 Flash exposes low, medium, high, while GPT-5.6 Sol exposes none, low, medium, high, xhigh, max.

Should I use Gemini 3.7 Flash or GPT-5.6 Sol?

We classify Gemini 3.7 Flash in the budget tier and GPT-5.6 Sol in the frontier tier. Test whether either meets your accuracy, tool-use and latency requirements before choosing on price.

Next step

Choosing between them

The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.

Input price: Gemini 3.7 Flash costs $0.75 per 1M tokens versus $4 for GPT-5.6 Sol — a 5.3x difference at the headline tier.
Context: GPT-5.6 Sol takes 1.05M against 1.05M for Gemini 3.7 Flash — only decisive if your prompts approach the smaller window.
Positioning: Gemini 3.7 Flash sits in the budget tier, GPT-5.6 Sol in the frontier tier. Compare accuracy, reliability, latency, and cost on representative tasks before choosing.

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