Model comparison
Gemini 3.7 Flash vs GPT-5.6 Sol
Google against OpenAI, compared on context, price, and verified benchmark results.
Catalog record checked August 14, 2026; individual provider fields may change.
Gemini 3.7 Flash
Budget
OpenAI
GPT-5.6 Sol
Frontier
| Specification | Gemini 3.7 Flash | GPT-5.6 Sol |
|---|---|---|
| Provider | OpenAI | |
| Tier | Budget | Frontier |
| Context window | 1.05M | Winner: 1.05M |
| Max output | 66K | Winner: 128K |
| Input / 1M tokens | Winner: $0.75 | $5 |
| Output / 1M tokens | Winner: $3.75 | $30 |
| Weights | Closed | Closed |
| Parameters | Not disclosed | Not disclosed |
| Reasoning levels | low, medium, high | none, low, medium, high, xhigh, max |
| Modalities | text, image, video, audio, pdf | text, image |
| Released | August 13, 2026 | July 9, 2026 |
| Artificial Analysis Intelligence Index [high] (2026-08-14) | 56 | Winner: 61 |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Pricing tiers: Gemini 3.7 Flash: Introductory paid-tier rates through 2026-12-31. From 2027-01-01 the standard paid rates are $1.50 / $7.50 per million tokens (Gemini API pricing). Cache is $0.075 / MTok through 2026-12-31, then $0.15. Wire calls to `gemini-3.7-flash`. Thinking levels are `low` / `medium` / `high` (API default medium; no MINIMAL). · GPT-5.6 Sol: Prompts above 272K tokens bill at 2× input and 1.5× output; cache writes are 1.25× the input rate.
Gemini 3.7 Flash
Google's 2026-08-13 Flash workhorse for coding and agents, three weeks after 3.6 Flash, at an introductory $0.75 / $3.75 per million tokens.
Best for
- Coding agents
- Multimodal agent loops
- High-volume Google API work
Watch out
Intro price doubles on 2027-01-01. DeepSWE 1.1 best-effort (high) is 65.3% at $2.18/task; medium scores 65.5% a few cents cheaper. 66K max output (65,536 tokens). Knowledge cutoff is March 2026 on some domains (January 2025 on others).
GPT-5.6 Sol
OpenAI's flagship tier, aimed at the hardest reasoning and agentic work.
Best for
- Complex reasoning
- Agentic workflows
- Hard coding tasks
Watch out
25x Luna's input price — overspecified for routine generation. Sol Fast mode (where offered) is roughly ~2× price for ~2.5× speed — only enable when latency is the constraint. `gpt-5.2-chat-latest` / `gpt-5.3-chat-latest` shut down 2026-08-10 — migrate API chat traffic to Sol. ChatGPT Plus/Pro Chat got an Aug 6 Sol refresh + effort slider; Work/Codex/API July builds are unchanged.
Benchmark
DeepSWE 1.1 in context
Both models shown against the wider field, with cost per completed task alongside the score.
Local leader
Claude Opus 5 [max]
74%
Rows shown
24
Highest published reasoning effort per model (not best Pass@1)
Snapshot date
2026-08-13
Mirrored from deepswe.datacurve.ai
Better is toward the top-right (higher pass rate, lower cost). X-axis is reversed to match DeepSWE’s public chart. v1.1 uses average cost / tokens / steps; v1 uses published medians.
| # | Model | Pass@1 | Cost / task | Tokens / task | Steps / task |
|---|---|---|---|---|---|
| 1 | Claude Opus 5 [max] | 74% | $11.84 | 118k | 99 |
| 2 | GPT-5.6 Sol [max] | 73% | $8.39 | 60k | 61 |
| 3 | Claude Fable 5 [max] | 70% | $21.63 | 119k | 88 |
| 4 | GPT-5.6 Terra [max] | 70% | $4.95 | 72k | 76 |
| 5 | Kimi K3 [max] | 69% | $4.65 | 82k | 98 |
| 6 | GPT-5.6 Luna [max] | 67% | $3.03 | 73k | 102 |
| 7 | GPT-5.5 [xhigh] | 67% | $7.23 | 46k | 82 |
| 8 | Grok 4.6 [xhigh] | 67% | $5.50 | 71k | 87 |
| 9 | Gemini 3.7 Flash [high] | 65% | $2.18 | 107k | 125 |
| 10 | DeepSeek V4-Pro [max] | 63% | $0.24 | 106k | 155 |
| 11 | Claude Opus 4.8 [max] | 59% | $13.22 | 135k | 120 |
| 12 | Qwen3.8-Max [xhigh] | 58% | $3.73 | 95k | 111 |
| 13 | Muse Spark 1.2 [xhigh] | 55% | $3.70 | 99k | 101 |
| 14 | Claude Sonnet 5 [max] | 54% | $26.40 | 214k | 268 |
| 15 | Grok 4.5 [high] | 54% | $2.42 | 36k | 61 |
| 16 | DeepSeek V4-Flash [max] | 53% | $0.10 | 108k | 153 |
| 17 | Muse Spark 1.1 [xhigh] | 53% | $2.36 | 74k | 96 |
| 18 | GPT-5.4 [xhigh] | 52% | $5.65 | 71k | 70 |
| 19 | Gemini 3.6 Flash [high] | 47% | $4.42 | 96k | 117 |
| 20 | GLM 5.2 [max] | 44% | $3.92 | 78k | 129 |
| 21 | Gemini 3.5 Flash [high] | 36% | $3.45 | 76k | 105 |
| 22 | Kimi K2.7 Code | 31% | $2.82 | 59k | 149 |
| 23 | Claude Sonnet 4.6 [high] | 30% | $5.52 | 76k | 134 |
| 24 | Gemini 3.1 Pro [high] | 12% | $2.14 | 28k | 76 |
DeepSWE “Best” picks the highest published reasoning effort per model (not the highest pass rate). Small gaps may not be statistically meaningful — confirm on deepswe.datacurve.ai.
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 $5 for GPT-5.6 Sol — roughly 6.7× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 3.7 Flash has tiered pricing: Introductory paid-tier rates through 2026-12-31. From 2027-01-01 the standard paid rates are $1.50 / $7.50 per million tokens (Gemini API pricing). Cache is $0.075 / MTok through 2026-12-31, then $0.15. Wire calls to `gemini-3.7-flash`. Thinking levels are `low` / `medium` / `high` (API default medium; no MINIMAL). GPT-5.6 Sol has tiered pricing: Prompts above 272K tokens bill at 2× input and 1.5× output; cache writes are 1.25× the input rate.
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 $30 for GPT-5.6 Sol — roughly 8.0× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Gemini 3.7 Flash has tiered pricing: Introductory paid-tier rates through 2026-12-31. From 2027-01-01 the standard paid rates are $1.50 / $7.50 per million tokens (Gemini API pricing). Cache is $0.075 / MTok through 2026-12-31, then $0.15. Wire calls to `gemini-3.7-flash`. Thinking levels are `low` / `medium` / `high` (API default medium; no MINIMAL). GPT-5.6 Sol has tiered pricing: Prompts above 272K tokens bill at 2× input and 1.5× output; cache writes are 1.25× the input rate.
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?
Gemini 3.7 Flash is the budget tier and GPT-5.6 Sol the frontier tier. The useful question is whether your hardest task actually fails on the cheaper one — most production volume such as classification, extraction and summarisation does not.
Next step
Choosing between them
Tier and workload decide this more reliably than a leaderboard position does.
If both sit in the same tier, the decision usually comes down to context window and output price rather than headline capability — output tokens dominate real bills.
If one is a step up within the same provider, the useful question is whether your hardest task actually fails on the cheaper tier. Most production volume — classification, extraction, summarization — does not.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Muse Code, or Lovable? Compare agentic harnesses · Latest releases.