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Home/Gemini 3.7 Flash vs GPT-5.6 Terra
Winner: GPT-5.6 TerraGoogle vs OpenAI

Gemini 3.7 Flash vs GPT-5.6 Terra

Gemini 3.7 Flash wins on price ($0.75 vs $2/1M input). GPT-5.6 Terra wins on coding (94 vs 89) and writing quality. For most workflows, GPT-5.6 Terra is the stronger default — best openai value — near-flagship capability at 60% off.

Last verified Aug 27, 2026/Model data modified Aug 27, 2026
Rankings refresh dailyScored on 6 criteriaNo paid rankings
OpenAIBalanced
Input cost
$2.00/1M
Context
1.1M tokens
Speed
Balanced

Clear recommendation block

The shortest way to see the safest default, the lower-cost option, and the specialist pick before you read deeper.

Best overall model

GPT-5.6 Terra

View
Why this recommendation

GPT-5.6 Terra is the safest overall answer here when you want the strongest default instead of the lowest list price.

OpenAIBalanced
Best for
High-volume production and enterprise workloads
Price
$2.00/1M
Context
1.1M tokens
Best budget model

Mistral: Mistral Nemo

View
Why this recommendation

Mistral: Mistral Nemo is the lower-cost option to start with when you still need useful output at scale.

MistralBudget
Best for
Teams needing a cheap, fast, multilingual workhorse for classification, summarization, or light coding tasks at scale.
Price
$0.02/1M
Context
131k tokens
Best for speed

Gemini 3.7 Flash

View
Why this recommendation

Gemini 3.7 Flash is the better pick when response speed matters more than maximum reasoning depth.

GoogleBalanced
Best for
High-volume coding and long-context work at introductory Flash pricing
Price
$0.75/1M
Context
1.0M tokens

Why this page recommends it

GPT-5.6 Terra leads on coding with a score of 94 vs 89 for Gemini 3.7 Flash.

GPT-5.6 Terra has the larger context window: 1.05M vs 1.048576M for Gemini 3.7 Flash.

Gemini 3.7 Flash is cheaper at $0.75/1M input tokens vs $2/1M for GPT-5.6 Terra.

Decision notes

Go with GPT-5.6 Terra if you want one model to handle coding and writing — it targets high-volume production and enterprise workloads.

Switch to Gemini 3.7 Flash when your work is mostly high-volume coding and long-context work at introductory Flash pricing; on that narrower brief it is the better tool.

Gemini 3.7 Flash is the more cost-efficient option at $0.75/1M input — GPT-5.6 Terra costs 3x more per input token, so the gap is worth taking seriously wherever token volume rather than peak quality drives the bill.

Interactive decision lab

Test the recommendation against your priority

Switch the scoring lens to see whether the top answer changes when you care more about cost, speed, or long-document work.

#1GPT-5.6 Terra89 pts
#2Gemini 3.7 Flash85 pts
Quality first

GPT-5.6 Terra

OpenAI / Balanced / Aug 6, 2026

89

Best OpenAI value — near-flagship capability at 60% off.

Ranks models by the broadest mix of coding, writing, research, and long-context usefulness.

Cost
$2.00/1M
$12.00/1M out
Speed
Balanced
3/5 score
Context
1.1M tokens
input window
View model
Data-backed recommendation
Avoid this pick if

You need Sol-level computer use or Opus 5-level repo engineering.

Recommended comparisons

The fastest way to see where the recommendation shifts when your priority changes.

GoogleBalancedWinner: GPT-5.6 Terra

Gemini 3.7 Flash

80.8% SWE-bench Verified at introductory Flash pricing.

Best use case
High-volume coding and long-context work at introductory Flash pricing
Input
$0.75/1M
Pricing
Balanced
Speed
Fast
Context
1.0M tokens
Coding1M contextFast
OpenAIBalancedOption 2

GPT-5.6 Terra

Best OpenAI value — near-flagship capability at 60% off.

Best use case
High-volume production and enterprise workloads
Input
$2.00/1M
Pricing
Balanced
Speed
Balanced
Context
1.1M tokens
ProductionCodingLong context

Side-by-side specs

Every figure below is the provider's list price or a published capability score — the same numbers the recommendation on this page is built from.

ModelInputOutputEst. monthContextSpeedCodingWritingResearch
GPT-5.6 TerraOpenAI$2.00/1M$12.00/1M$441.1M tokensBalanced949293
Gemini 3.7 FlashGoogle$0.75/1M$3.75/1M$151.0M tokensFast898285

Capability scores are out of 100 and reflect our own weighting of published benchmarks and production signals — see how we evaluate models. “Est. month” assumes 10M input and 2M output tokens at list price, with no batch or caching discounts applied, so treat it as a ceiling.

The case for each model

What each one is genuinely good at, where it falls down, and the situations we would steer you away from it — not just the headline score.

GPT-5.6 Terra

Winner: GPT-5.6 TerraOpenAI

The balanced mid-tier of the GPT-5.6 family — GPT-5.5-class capability at a fraction of the price, built for production workloads at scale.

Input
$2.00/1M
Output
$12.00/1M
Context
1.1M tokens
Speed
Balanced

What people actually use it for

  • Production coding assistance within 1–4 points of flagship Sol at 60% lower output cost
  • Long-document pipelines — 72.5% recall on 512K–1M token tasks, nearly matching Sol
  • Enterprise workloads that previously ran on GPT-5.5 at $5/$30, now ~half price

Where it wins

  • Within 1–4 points of Sol on core benchmarks (SWE-bench Pro 63.4%, Terminal-Bench 2.1 87.4%, GPQA Diamond 92.9%) at $2/$12
  • Strong long-context recall: 72.5% on 512K–1M tasks vs Luna's 41.3% collapse
  • July 30, 2026 price cut made it ~2x cheaper than GPT-5.5 for comparable capability

Where it falls down

  • Big gap to Sol on computer use (OSWorld 50.2% vs 62.6%) — not a drop-in Sol replacement for agents
  • Well behind Claude Opus 5 on repository-level coding (SWE-bench Pro ~63% vs 79.2%)

Skip it if

You need Sol-level computer use or Opus 5-level repo engineering.

Our verdict

The sensible OpenAI default for production. Terra delivers ~97% of Sol's benchmark line at 40% of the output price, making GPT-5.5's rate card look obsolete. Pick Sol only for computer-use agents and the hardest reasoning.

Launched at $2.50/$15, cut to $2/$12 on July 30, 2026. Long-context above 272K: $4/$18. Part of the government-reviewed GPT-5.6 family, fully public July 9, 2026.

Gemini 3.7 Flash

Google

Google's fastest-moving coding workhorse — 80.8% on SWE-bench Verified at half the price of Gemini 3.6 Flash, shipped just three weeks after it.

Input
$0.75/1M
Output
$3.75/1M
Context
1.0M tokens
Speed
Fast

What people actually use it for

  • Bulk code review and refactoring where 80.8% SWE-bench Verified is enough and volume matters
  • 1M-context document and repository analysis at $0.75/1M input
  • Agentic loops that need frontier-adjacent coding quality without frontier pricing

Where it wins

  • 80.8% on SWE-bench Verified — frontier-class coding from a Flash-tier model
  • Large jumps over 3.6 Flash on software engineering: FrontierCode 34.4% to 43.6%, DeepSWE 49.0% to 65.3%
  • Artificial Analysis Intelligence Index of 56 at high thinking level, with a 1M token context window

Where it falls down

  • The $0.75/$3.75 launch price is introductory — it doubles to $1.50/$7.50 on January 1, 2027
  • Still short of Claude Opus 5 (96%) and GPT-5.6 Sol (96.2%) on SWE-bench Verified for the hardest coding work

Skip it if

You are planning 2027 spend and need price certainty — the introductory rate expires December 31, 2026.

Our verdict

The best coding score per dollar in Google's lineup right now — 80.8% SWE-bench Verified at $0.75/1M input. Budget on the post-January 2027 price of $1.50/$7.50 if you are signing anything long-term.

Released August 13, 2026, only three weeks after Gemini 3.6 Flash. Introductory pricing of $0.75/$3.75 runs through December 31, 2026; on January 1, 2027 it doubles to $1.50/$7.50, which is exactly Gemini 3.6 Flash's rate.

Explore related decisions

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Comparison
GPT-5.6 Sol vs GPT-5.6 TerraGPT-5.6 Sol vs GPT-5.6 Terra — see exactly which wins on SWE-bench coding, price per 1M tokens, context window, and speed, with a clear verdict for every use…Read guide
Comparison
GPT-5.6 Terra vs GPT-5.5GPT-5.6 Terra vs GPT-5.5 — see exactly which wins on SWE-bench coding, price per 1M tokens, context window, and speed, with a clear verdict for every use case.Read guide
Google
Gemini 3.7 Flash80.8% SWE-bench Verified at introductory Flash pricing.Read guide
OpenAI
GPT-5.6 TerraBest OpenAI value — near-flagship capability at 60% off.Read guide
Alternatives
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Quick links

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FAQ

Is Gemini 3.7 Flash better than GPT-5.6 Terra?

GPT-5.6 Terra wins on more of the categories we score — coding, writing, research — so it is the better default of the two. Gemini 3.7 Flash is the better pick when your work is mostly high-volume coding and long-context work at introductory Flash pricing. Neither is universally "better": GPT-5.6 Terra is aimed at high-volume production and enterprise workloads, Gemini 3.7 Flash at high-volume coding and long-context work at introductory Flash pricing.

Which is cheaper — Gemini 3.7 Flash or GPT-5.6 Terra?

Gemini 3.7 Flash is cheaper at $0.75/1M input and $3.75/1M output. GPT-5.6 Terra costs $2/1M input and $12/1M output.

Which has a larger context window — Gemini 3.7 Flash or GPT-5.6 Terra?

GPT-5.6 Terra has the larger context window at 1.05M tokens vs Gemini 3.7 Flash's 1.048576M. For large document analysis, GPT-5.6 Terra is the stronger pick.

Is Gemini 3.7 Flash or GPT-5.6 Terra better for coding?

GPT-5.6 Terra is better for coding with a score of 94 vs Gemini 3.7 Flash's 89 (out of 100). Claude Fable 5 is the overall coding leader in this directory at 100/100.

Which is faster — Gemini 3.7 Flash or GPT-5.6 Terra?

Gemini 3.7 Flash is faster with a fast speed rating (score: 4) vs GPT-5.6 Terra's balanced rating (score: 3). Speed matters most for interactive and high-throughput work; for batch jobs the GPT-5.6 Terra latency penalty is usually invisible.

What are the downsides of GPT-5.6 Terra?

Big gap to Sol on computer use (OSWorld 50.2% vs 62.6%) — not a drop-in Sol replacement for agents. Well behind Claude Opus 5 on repository-level coding (SWE-bench Pro ~63% vs 79.2%). Avoid it if you need Sol-level computer use or Opus 5-level repo engineering. That is the main case for looking at Gemini 3.7 Flash instead.

What are the downsides of Gemini 3.7 Flash?

The $0.75/$3.75 launch price is introductory — it doubles to $1.50/$7.50 on January 1, 2027. Still short of Claude Opus 5 (96%) and GPT-5.6 Sol (96.2%) on SWE-bench Verified for the hardest coding work. Avoid it if you are planning 2027 spend and need price certainty — the introductory rate expires December 31, 2026. Against GPT-5.6 Terra specifically, the gap shows up most on coding (94 vs 89).

What does a month of real work cost on Gemini 3.7 Flash vs GPT-5.6 Terra?

Take a moderate workload of 10M input and 2M output tokens a month. Gemini 3.7 Flash runs $15.00 (at $0.75/1M in and $3.75/1M out); GPT-5.6 Terra runs $44.00 (at $2/1M in and $12/1M out). That is a $29.00/month difference — Gemini 3.7 Flash is the cheaper of the two at this volume, and the gap scales linearly as you send more. Output tokens dominate the bill on both, so prompt length matters far less than response length.

Can I use Gemini 3.7 Flash and GPT-5.6 Terra together?

Yes, and for most teams that beats picking one. A common split is GPT-5.6 Terra for high-volume production and enterprise workloads, with Gemini 3.7 Flash handling high-volume coding and long-context work at introductory Flash pricing. Routing high-volume, low-stakes calls to Gemini 3.7 Flash at $0.75/1M and reserving GPT-5.6 Terra for the hard cases is usually the cheapest arrangement that does not cost you quality.