Model comparison
Gemini 3.5 Flash vs GPT-5.6 Terra
Google against OpenAI, compared on context, price, and verified benchmark results.
Catalog record checked September 3, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
Gemini 3.5 Flash
Balanced
OpenAI
GPT-5.6 Terra
Balanced
| Specification | Gemini 3.5 Flash | GPT-5.6 Terra |
|---|---|---|
| Provider | OpenAI | |
| Tier | Balanced | Balanced |
| Context window | 1M | Winner: 1.05M |
| Max output | 64K | Winner: 128K |
| Input / 1M tokens | Winner: $1.50 | $2 |
| Output / 1M tokens | Winner: $9 | $12 |
| Weights | Closed | Closed |
| Parameters | Not disclosedUnverified | mid-tier reasoning model |
| Reasoning levels | low, medium, high | none, low, medium, high, xhigh, max |
| Modalities | text, image, video, audio, pdf | text, image |
| API model id | gemini-3.5-flash | gpt-5.6-terra |
| Released | May 19, 2026 | July 9, 2026 |
| Artificial Analysis Intelligence Index (2026-08-14) | 53 | Not verifiedUnverified |
| Artificial Analysis Intelligence Index [high] (2026-08-14) | Not verifiedUnverified | 50 |
| SWE-bench Verified (2026-09-01) | Not verifiedUnverified | 95.4 |
| Terminal-Bench 2.1 (2026-07-09) | Not verifiedUnverified | 87.4 |
| LiveBench (2026-09-05) | Not verifiedUnverified | 77.9 |
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.
Benchmark receipts
- 2026-09-05: LiveBench official leaderboard (benchmark-owned), max effortContamination-resistant general capability across reasoning, coding, math, data analysis, and language, with monthly question refreshes. Comparability: comparable with caveat — Rolling question set: observations months apart measure different question mixes. Record the measurement date and compare within ~1 month windows.
- 2026-09-01: vals.ai SWE-bench Verified leaderboard (independent, mini-swe-agent bash-only) (independent; official SWE-bench not published)Real GitHub issue resolution: does the model's patch pass the hidden tests. Comparability: comparable with caveat — Post-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.
- 2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
- 2026-07-09: OpenAI GPT-5.6 announcement (vendor; chart transcribed by Vellum)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
Pricing tiers: Gemini 3.5 Flash: $1.50/$9.00 per MTok (single aggregator source — verify before publishing). Multimodal input. · GPT-5.6 Terra: Launch list was $2.50/$15; cut to $2/$12 on 2026-07-30. Cached input $0.20/MTok; batch $1/$6.
Gemini 3.5 Flash
Gemini 3.5 Flash is Google's agent-focused Flash tier launched at Google I/O 2026.
Best for
- Agentic workflows
- Multimodal input
- High-volume work
Watch out
Price is single-source; confirm on Google Cloud before relying on it.
GPT-5.6 Terra
GPT-5.6 Terra delivers roughly GPT-5.5-class quality at about half the cost, with the full 1.05M-token context.
Best for
- Cost-sensitive production
- Mixed reasoning workloads
- High-volume agents
Watch out
Quality trails Sol on the hardest tasks; route frontier work to Sol when it matters.
When the cheaper one wins
Gemini 3.5 Flash is cheaper on output at $9 per million tokens against $12 for GPT-5.6 Terra — about 1.3×. 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. These are standard-tier API rates, excluding batch and cache discounts.
Run the model pickerEvidence confidence: High
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.
- 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
- Verified within the last 90 days — Newest catalog check was 8 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 3.5 Flash: Google — Gemini 3.5 Flash (accessed 2026-08-29)
- Gemini 3.5 Flash: Google Cloud Gemini pricing (accessed 2026-08-29)
- GPT-5.6 Terra: OpenAI — GPT-5.6 (accessed 2026-08-29)
- GPT-5.6 Terra: OpenAI API pricing (gpt-5.6-terra $2/$12) (accessed 2026-08-29)
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- Cohere Command A+ vs Gemini 3.5 Flash
- Cohere Command A+ vs GPT-5.6 Terra
Diving deeper on one model? Gemini 3.5 Flash · GPT-5.6 Terra
Common questions
Gemini 3.5 Flash vs GPT-5.6 Terra
Answered from the verified figures on this page rather than general guidance.
Is Gemini 3.5 Flash or GPT-5.6 Terra cheaper for input?
Gemini 3.5 Flash is cheaper at $1.50 per million input tokens, against $2 for GPT-5.6 Terra — roughly 1.3× 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 3.5 Flash has tiered pricing: $1.50/$9.00 per MTok (single aggregator source — verify before publishing). Multimodal input. GPT-5.6 Terra has tiered pricing: Launch list was $2.50/$15; cut to $2/$12 on 2026-07-30. Cached input $0.20/MTok; batch $1/$6.
Is Gemini 3.5 Flash or GPT-5.6 Terra cheaper for output?
Gemini 3.5 Flash is cheaper at $9 per million output tokens, against $12 for GPT-5.6 Terra — roughly 1.3× 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 3.5 Flash has tiered pricing: $1.50/$9.00 per MTok (single aggregator source — verify before publishing). Multimodal input. GPT-5.6 Terra has tiered pricing: Launch list was $2.50/$15; cut to $2/$12 on 2026-07-30. Cached input $0.20/MTok; batch $1/$6.
Which has the larger context window, Gemini 3.5 Flash or GPT-5.6 Terra?
GPT-5.6 Terra accepts 1.05M tokens against 1M for Gemini 3.5 Flash. This only matters if you routinely send very long documents or large codebases.
Do Gemini 3.5 Flash and GPT-5.6 Terra support the same reasoning levels?
Gemini 3.5 Flash exposes low, medium, high, while GPT-5.6 Terra exposes none, low, medium, high, xhigh, max.
Should I use Gemini 3.5 Flash or GPT-5.6 Terra?
Both sit in the balanced tier, so the choice usually comes down to price and context rather than capability. Gemini 3.5 Flash suits agentic workflows; GPT-5.6 Terra suits cost-sensitive production.
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: Gemini 3.5 Flash costs $1.50 per 1M tokens versus $2 for GPT-5.6 Terra — a 1.3x difference at the headline tier.
- Context: GPT-5.6 Terra takes 1.05M against 1M for Gemini 3.5 Flash — only decisive if your prompts approach the smaller window.
- Measured capability: Gemini 3.5 Flash leads Artificial Analysis Intelligence Index 53 to 50 (measured 2026-08-14).
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