GPT-5.6 Sol vs Gemini 3.1 Flash-Lite
OpenAI's GPT-5.6 Sol and Google's Gemini 3.1 Flash-Lite both target production language workloads, but they price and behave differently. Here is the side-by-side.
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The short answer
Gemini 3.1 Flash-Lite is the cheaper option — roughly 14.2x less on a blended workload, and it suits ultra-cheap high-volume tasks. GPT-5.6 Sol justifies its premium when you need frontier coding and long-horizon agents. Only GPT-5.6 Sol does native reasoning, which matters for multi-step tasks but adds billable thinking tokens.
OpenAI • GPT-5.6
$4.00 / $20.00
/ 1M tokens (input / output)
OpenAI's flagship tier and the current state of the art on agentic coding benchmarks. Reasoning effort is tunable from none through max, and an `ultra` setting coordinates parallel subagents across workstreams. Sol reaches near-Fable-5 intelligence while spending markedly fewer output tokens, which is why its cost per finished task lands well below its sticker price.
Google • Gemini 3.1
$0.25 / $1.50
/ 1M tokens (input / output)
Google's efficiency tier and a long-term stable target, priced for workloads measured in millions of calls rather than thousands. It gives up the deeper reasoning of 3.5 Flash, so it suits mechanical tasks — classification, extraction, moderation — where a million tokens of context still helps but chain-of-thought does not.
Input price
Gemini 3.1 Flash-Lite is 94% cheaper than GPT-5.6 Sol on input tokens.
Output price
Gemini 3.1 Flash-Lite is 93% cheaper than GPT-5.6 Sol on output tokens — usually the side that dominates the bill.
Monthly cost at three workload sizes
Standard (non-batch, non-cached) rates. Reasoning models will exceed these figures because thinking tokens bill as output.
| Workload | GPT-5.6 Sol | Gemini 3.1 Flash-Lite | Difference |
|---|---|---|---|
| Light — 1M in / 200K out | $8 | $1 | $7 |
| Moderate — 10M in / 2M out | $80 | $6 | $75 |
| Heavy — 100M in / 20M out | $800 | $55 | $745 |
Specification comparison
| Attribute | GPT-5.6 Sol | Gemini 3.1 Flash-Lite |
|---|---|---|
| Input (/ 1M tokens) | $4.00 | $0.25 |
| Output (/ 1M tokens) | $20.00 | $1.50 |
| Cached input | $0.40 | — |
| Context window | 1,048,576 tokens | 1,048,576 tokens |
| Max output | 128,000 tokens | 65,536 tokens |
| Native reasoning | Yes | No |
| Knowledge cutoff | 2026-02 | 2025-01 |
| Relative latency | high | low |
| Open weights | No | No |
| API model ID | gpt-5.6-sol | gemini-3.1-flash-lite |
| Status | stable | stable |
GPT-5.6 Sol: Promotional pricing (down from $5/$30) held at least through 2026-11-21. Prompts above 272K input tokens bill at higher rates; 'fast' processing is 2x.
Choose GPT-5.6 Sol if…
- Long-running autonomous coding agents
- Large-scale refactors and migrations
- Agentic browsing and computer use
- Scientific and financial analysis
Choose Gemini 3.1 Flash-Lite if…
- Content moderation at volume
- Classification and routing
- Lightweight summarization
- Cheap long-context retrieval
Frequently asked
Is GPT-5.6 Sol or Gemini 3.1 Flash-Lite cheaper?
Gemini 3.1 Flash-Lite is cheaper. On a blended 3:1 input-to-output workload it costs about 14.2x less than GPT-5.6 Sol.
Which has the larger context window, GPT-5.6 Sol or Gemini 3.1 Flash-Lite?
Both accept up to 1.05M tokens, so context is not a differentiator here.
Should I use GPT-5.6 Sol or Gemini 3.1 Flash-Lite?
Pick GPT-5.6 Sol for frontier coding and long-horizon agents. Pick Gemini 3.1 Flash-Lite for ultra-cheap high-volume tasks. If cost dominates the decision, Gemini 3.1 Flash-Lite wins; if you need the capability ceiling, benchmark both on your own evals before committing.