Is Gemini 3.5 Flash better than GPT-5.6 Terra?

Gemini 3.5 Flash (high) and GPT-5.6 Terra (max) are neck and neck on quality (63.1 vs 64.4, within the ±5.7 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-25, so check the category scores for your use.

Which is cheaper, Gemini 3.5 Flash or GPT-5.6 Terra, and will that change?

Gemini 3.5 Flash is cheaper today: $3.38 against $4.50 per million tokens, blended at three input tokens per output token. No price change has been announced for either.

Is Gemini 3.5 Flash better than GPT-5.6 Terra for coding?

GPT-5.6 Terra scores higher in coding (65 vs 60 on the category index, where 50 is average). On SciCode, the top shared coding benchmark, it is 53.9% for Gemini 3.5 Flash against 55.0% for GPT-5.6 Terra.

Is Gemini 3.5 Flash better than GPT-5.6 Terra for agents and tool use?

Gemini 3.5 Flash scores higher in agentic tasks (63 vs 59 on the category index, where 50 is average). On τ³-Banking (AA), the top shared agents & tools benchmark, it is 32.2% for Gemini 3.5 Flash against 40.2% for GPT-5.6 Terra.

Which is better for long documents?

GPT-5.6 Terra scores higher on long-context benchmarks (67 vs 62). Both take about 1.1M tokens: Gemini 3.5 Flash 1,048,576, GPT-5.6 Terra 1,050,000.

Which has lower latency?

Gemini 3.5 Flash (high) answers first: 14.2 s against 101.0 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.

Which is faster, Gemini 3.5 Flash or GPT-5.6 Terra?

Gemini 3.5 Flash streams faster: 222 against 126 output tokens per second.

When was GPT-5.6 Terra released?

GPT-5.6 Terra was released on 9 Jul 2026.

Gemini 3.5 Flash vs GPT-5.6 Terra

Full profiles: Gemini 3.5 Flash (Google) and GPT-5.6 Terra (OpenAI): every benchmark, price and rank.

Updated 25 Oct 2026 · Data from 10 sources

As of 25 Oct 2026, Gemini 3.5 Flash (high) and GPT-5.6 Terra (max) are neck and neck on quality (63.1 vs 64.4 on the BenchLeader Index, inside the ±5.7 margin of error), and Gemini 3.5 Flash (high) costs 1.3× less, which makes it the better buy for most workloads. Pick Gemini 3.5 Flash for knowledge (65 vs 57); pick GPT-5.6 Terra for maths (69 vs 58).

Gemini 3.5 Flash benchmarks high Google

GPT-5.6 Terra benchmarks max OpenAI Open in the comparison tool

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use case	Pick	Why	Confidence
Coding	GPT-5.6 Terra	65 vs 60 category score; SciCode 55.0% vs 53.9%	Medium
Agents & tool use	Gemini 3.5 Flash	63 vs 59 category score; τ³-Banking (AA) 32.2% vs 40.2%	Medium
Maths	GPT-5.6 Terra	69 vs 58 category score; FrontierMath Tiers 1–3 86.0% vs 62.8%	High
Reasoning	GPT-5.6 Terra	70 vs 61 category score; GPQA Diamond 93.3% vs 92.8%	High
Knowledge	Gemini 3.5 Flash	65 vs 57 category score; SimpleQA Verified 66.2% vs 43.2%	High
Long documents	GPT-5.6 Terra	67 vs 62 category score; AA-LCR 83.0% vs 73.3%	Medium
Images and other media	Gemini 3.5 Flash	67 vs 64 category score; MMMU-Pro 84.3% vs 80.7%	Medium
Following instructions	Gemini 3.5 Flash	74 vs 70 category score; IFBench 76.3% vs 71.2%	Medium
Chat quality (human preference)	–	Only Gemini 3.5 Flash has an Arena rating (67 category score)	Not comparable
Lowest cost	Gemini 3.5 Flash	$3.38 vs $4.50 per 1M blended; agentic coding session $0.126 vs $0.168	–
Fastest first answer	Gemini 3.5 Flash	14.2 s (Gemini 3.5 Flash (high)) vs 101.0 s (GPT-5.6 Terra (max)) to the first answer token	–
High volume on a budget	Neither flagship	A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs	–

Key differences

Gemini 3.5 Flash (high) and GPT-5.6 Terra (max) are neck and neck on quality (63.1 vs 64.4, within the ±5.7 margin).
Gemini 3.5 Flash (high) is stronger in agents & tools, human preference, instruction following, knowledge, multimodal.
GPT-5.6 Terra (max) is stronger in coding, composite, long context, maths, reasoning.
Gemini 3.5 Flash (high) is 1.3× cheaper ($3.38 vs $4.50 per 1M blended).
Gemini 3.5 Flash (high) streams 1.8× faster (222 vs 126 tokens per second).

At a glance

Spec	Gemini 3.5 Flash	GPT-5.6 Terra
Developer	Google	OpenAI
Released	19 May 2026	9 Jul 2026
Context window (tokens)	1,048,576	1,050,000
Compared at	Gemini 3.5 Flash (high)	GPT-5.6 Terra (max)
Open weights	No	No
Price in / out / cached input per 1M	$1.50 / $9.00 / $0.150	$2.00 / $12.00 / $0.200

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

Category	Gemini 3.5 Flash (high)	GPT-5.6 Terra (max)	Leader
Reasoning	61.3	70.1	GPT-5.6 Terra
Coding	59.8	65.1	GPT-5.6 Terra
Agents & tools	63.4	58.9	Gemini 3.5 Flash
Maths	58.3	68.9	GPT-5.6 Terra
Knowledge	65.2	57.2	Gemini 3.5 Flash
Instruction following	74.3	69.9	Gemini 3.5 Flash
Human preference	66.8	–	not comparable
Multimodal	66.6	63.7	Gemini 3.5 Flash
Long context	61.6	66.6	GPT-5.6 Terra
Composite	65.9	76.6	GPT-5.6 Terra

Where sources disagree

Across the 59 benchmarks both have, Gemini 3.5 Flash leads 16, GPT-5.6 Terra leads 43. Independent sources split: Gemini 3.5 Flash leads on Arena Text; GPT-5.6 Terra leads on AA Intelligence Index v4.3.2.

Overall index	Gemini 3.5 Flash (high)	GPT-5.6 Terra (max)	Leader
BenchLeader Index	63.1	64.4	neck and neck
AA Intelligence Index v4.3.2	32.6	42.1	GPT-5.6 Terra
Arena Text	1477	1467†	Gemini 3.5 Flash

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.

Measure	Gemini 3.5 Flash (high)	GPT-5.6 Terra (max)
Blended price per 1M tokens	$3.38	$4.50
Input / output per 1M	$1.50 / $9.00	$2.00 / $12.00
Cached input per 1M	$0.150	$0.200
Price per task: chat reply	$0.0033	$0.0044
Price per task: summarize a 30-page report	$0.023	$0.031
Price per task: code edit	$0.022	$0.030
Price per task: agentic coding session	$0.126	$0.168
Price per task: structured extraction	$0.0048	$0.0064
Cost to run a full benchmark suite	$3.69	$1.40
Output speed	222 tok/s	126 tok/s
Time to first answer	14.2 s	101.0 s
Time to a complete answer	16.4 s	105.0 s

Per token is not per task: on Artificial Analysis' full suite Gemini 3.5 Flash (high) cost $3.69 and GPT-5.6 Terra (max) $1.40, because Gemini 3.5 Flash (high) used about 3.5× as many tokens for the same work, which a per-token price hides.

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.5 Flash (high) scores 63.1 and takes 14 s to its first answer token; Gemini 3.5 Flash (medium) scores 62.8 in 12 s, Gemini 3.5 Flash (minimal) scores 56.4 in 1 s. GPT-5.6 Terra (max) scores 64.4 and takes 101 s to its first answer token; GPT-5.6 Terra (xhigh) scores 62.8 in 7 s, GPT-5.6 Terra (high) scores 61.3 in 2 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

128 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

Metric	Publisher	Gemini 3.5 Flash (high)	GPT-5.6 Terra (max)
BenchLeader Index	BenchLeader	63.1	64.4
Agents & tools score	BenchLeader	63.4	58.9
Coding score	BenchLeader	59.8	65.1
Composite score	BenchLeader	65.9	76.6
Human preference score	BenchLeader	66.8	–
Instruction following score	BenchLeader	74.3	69.9
Knowledge score	BenchLeader	65.2	57.2
Long context score	BenchLeader	61.6	66.6
Maths score	BenchLeader	58.3	68.9
Multimodal score	BenchLeader	66.6	63.7
Reasoning score	BenchLeader	61.3	70.1
Blended price $/M	BenchLeader	$3.38	$4.50
Output speed	BenchLeader	222 tok/s	126 tok/s
Time to first answer	BenchLeader	14.2 s	101.0 s
Context window	BenchLeader	1,048,576 tokens	1,050,000 tokens
Reasoning
GPQA Diamond	Epoch AI Benchmarking Hub	92.8%	93.3%
SimpleBench	SimpleBench	76.7%†	48.9%†
Arena Hard Prompts	Arena (LMArena)	1495	1490†
LiveBench 2.0 Reasoning	LiveBench	–	90.6%†
LiveBench 1.0 Reasoning	LiveBench	82.0%	90.6%
GPQA Diamond (AA)	Artificial Analysis	92.2%	92.5%
Humanity's Last Exam (AA)	Artificial Analysis	42.7%	42.9%
GPQA Diamond (Vals)	Vals AI	92.7%	90.9%†
EnigmaEval	Scale AI SEAL	25.4%	–
Kagi LLM Benchmark	Kagi LLM Benchmark	–	51.3%†
ARC-AGI-1	ARC Prize	92.5%	96.5%
ARC-AGI-2	ARC Prize	72.1%	83.9%
ARC-AGI-3	ARC Prize	–	0.8%
CritPt	Artificial Analysis	13.1%	30.0%
Chess Puzzles	Epoch AI Benchmarking Hub	45.0%	47.0%
Mystery Game Puzzles	Epoch AI Benchmarking Hub	32.0%	35.0%
LMCA	Epoch AI Benchmarking Hub	47.1%	55.0%
DTBench	Epoch AI Benchmarking Hub	94.7%	93.3%
ForecastBench	ForecastBench	64.3%†	–
Coding
SWE-bench Verified (Epoch)	Epoch AI Benchmarking Hub	79.3%	–
SciCode	SciCode	53.9%	55.0%
WeirdML	WeirdML	62.6%	78.3%†
FrontierCode	Cognition	–	41.3%†
Arena Coding	Arena (LMArena)	1508	1518†
Arena WebDev	Arena (LMArena)	1499	1521†

Show all 128 benchmarks

Metric	Publisher	Gemini 3.5 Flash (high)	GPT-5.6 Terra (max)
Coding
LiveBench 2.0 Coding	LiveBench	–	86.2%†
LiveBench 1.0 Coding	LiveBench	78.2%	78.3%
LiveCodeBench	Vals AI	87.6%	85.9%†
IOI	Vals AI	–	87.6%
SWE-bench (Vals)	Vals AI	78.8%	95.4%
Code Migration	Vals AI	26.8%	47.8%
ProgramBench	Vals AI	0.0%	0.5%
Vibe Code Bench 1-100	Vals AI	–	14.8%
Vibe Code Bench v1.1	Vals AI	48.7%	74.6%
Surface Evolver Bench	Epoch AI Benchmarking Hub	58.1%†	83.8%†
DeepSWE v1.1	Epoch AI Benchmarking Hub	36.1%	69.6%
CursorBench	Cursor	–	41.3%
ALE-Bench	Epoch AI Benchmarking Hub	911.0	1951.4
Terminal-Bench 4.0 (AA)	Artificial Analysis	6.6%	35.4%
Terminal-Bench 2.1 (AA)	Artificial Analysis	78.7%	88.0%
Startrise Frontend	Startrise	–	66.9%†
Agents & tools
Terminal-Bench	Terminal-Bench	–	21.5%
APEX-Agents	Mercor	27.5%†	58.2%
Arena Agent	Arena (LMArena)	–	0.2†
LiveBench Long Agentic	LiveBench	–	48.4%†
LiveBench Browser	LiveBench	–	84.0%†
LiveBench Agentic Coding	LiveBench	49.0%	55.0%
Terminal-Bench Hard	Artificial Analysis	40.9%	57.6%
τ²-Bench Telecom (AA)	Artificial Analysis	95.3%	86.3%
Terminal-Bench 2.1 (Vals)	Vals AI	74.2%	77.5%
MCP Atlas	Scale AI SEAL	83.6%	–
HiL-Bench	Scale AI SEAL	27.7%†	–
GDPval-AA v2.1	Artificial Analysis	–	47.6%
τ³-Banking (AA)	Artificial Analysis	32.2%	40.2%
ITBench SRE (AA)	Artificial Analysis	40.4%	51.0%
Analyst Agent (AA)	Artificial Analysis	45.0%	–
APEX-Agents (AA)	Artificial Analysis	47.0%	38.9%
CyberBench	Vals AI	–	72.1%
Finance Agent v2	Vals AI	57.9%	54.4%
Harvey's Legal Agent Benchmark v1	Vals AI	2.5%	0.8%
Legal Research Bench	Vals AI	30.8%	41.4%
SkillsBench	Vals AI	52.7%	58.9%
SREBench	Vals AI	–	9.5%
Tax Agent Bench	Vals AI	21.6%	30.0%
Terminal-Bench 2.0 (Vals)	Vals AI	67.4%	–
Terminal-Bench 4.0 (Vals)	Vals AI	6.1%	22.7%
Terminal-Bench Science	Vals AI	5.7%	10.0%
Web Search Index	Vals AI	37.0%	–
BALROG	BALROG	–	53.2%
GBAEval	Epoch AI Benchmarking Hub	6.7%†	–
Vending-Bench 2	Andon Labs	5396.4†	7343.2†
AutomationBench	Artificial Analysis	42.1%	59.6%
GDP.pdf (AA)	Artificial Analysis	19.8%	24.0%
EnterpriseOps-Gym	Artificial Analysis	50.1%	38.5%
AA-Briefcase v1.1	Artificial Analysis	874	–
Terminal-Bench-Science 0.1 (AA)	Artificial Analysis	–	13.8%
FACTS Search	Google	64.3%†	81.7%†
Maths
FrontierMath Tiers 1–3	Epoch AI Benchmarking Hub	62.8%	86.0%
FrontierMath Tier 4	Epoch AI Benchmarking Hub	26.8%	70.7%
OTIS Mock AIME	Epoch AI Benchmarking Hub	95.6%	99.7%
ProofBench	Vals AI	31.0%	74.0%†
LiveBench Mathematics	LiveBench	88.2%	94.9%
AIME 2026	MathArena	95.0%†	–
HMMT February 2026	MathArena	95.5%†	–
MathArena Apex	MathArena	32.3%†	–
Arena Maths	Arena (LMArena)	1497	1483†
Knowledge
SimpleQA Verified	Epoch AI Benchmarking Hub	66.2%	43.2%
LiveBench 2.0 Data Analysis	LiveBench	–	79.3%†
LiveBench Research	LiveBench	–	60.4%†
LiveBench 1.0 Data Analysis	LiveBench	64.9%	79.3%
AA-Omniscience	Artificial Analysis	21.2	0.1
MMLU-Pro	Vals AI	89.5%	86.7%†
LegalBench	Vals AI	83.6%	85.1%
CorpFin	Vals AI	64.7%	65.3%†
TaxEval	Vals AI	74.4%	76.2%†
Excel Modeling Benchmark	Vals AI	63.5%	66.2%
MedCode	Vals AI	55.8%	43.4%†
MedScribe	Vals AI	76.6%	82.9%†
Public Benefits Bench v1.1	Vals AI	59.5%	62.4%
DrugDiscoveryBench	Scale AI SEAL	50.0%	–
EBR-bench	Epoch AI Benchmarking Hub	4.8%	–
GDP.pdf	Epoch AI Benchmarking Hub	14.0%†	24.7%†
AA-Omniscience: accuracy	Artificial Analysis	51.4%	46.8%
AA-Omniscience: non-hallucination	Artificial Analysis	37.8%	12.1%
Instruction following
LiveBench Language	LiveBench	84.6%	82.9%
LiveBench Instruction Following	LiveBench	75.6%	64.6%
IFBench	Artificial Analysis	76.3%	71.2%
Arena Instruction Following	Arena (LMArena)	1465	1464†
Human preference
Arena Text	Arena (LMArena)	1477	1467†
EQ-Bench 4	EQ-Bench	1081†	1224†
Arena Creative Writing	Arena (LMArena)	1464	1429†
Arena Multi-turn	Arena (LMArena)	1480	1472†
Arena Longer Queries	Arena (LMArena)	1482	1468†
Multimodal
Arena Vision	Arena (LMArena)	1308	1271†
LiveBench Design	LiveBench	–	76.0%†
MMMU-Pro	Artificial Analysis	84.3%	80.7%
MMMU-Pro (Vals)	Vals AI	88.3%	86.5%
MortgageTax	Vals AI	68.1%	67.3%†
SAGE	Vals AI	49.9%	47.0%
Blueprint-Bench 2	Epoch AI Benchmarking Hub	33.6%†	30.8%†
Long context
AA-LCR	Artificial Analysis	73.3%	83.0%
Arena Document	Arena (LMArena)	1453	1477†
MLCR	Artificial Analysis	10.0%	27.2%
Composite
Epoch Capabilities Index	Epoch AI Benchmarking Hub	154.9†	160.1†
LiveBench 2.0	LiveBench	–	75.0%†
LiveBench 1.0	LiveBench	74.6%	77.9%
AA Intelligence Index v4.3.2	Artificial Analysis	32.6	42.1
Vals Multimodal Index	Vals AI	62.9%	65.1%†

Data as of 2026-10-25. Best configuration of each model; every score links to its source on the model pages.

What changed

23 Oct 2026 Gemini 3.5 Flash (high): 1 new result (Harvey's Legal Agent Benchmark v1).
23 Oct 2026 GPT-5.6 Terra (max): 1 new result (Harvey's Legal Agent Benchmark v1).
21 Oct 2026 Gemini 3.5 Flash (high): 1 score revision.
21 Oct 2026 GPT-5.6 Terra (max): 1 score revision.
19 Oct 2026 Gemini 3.5 Flash (high): BenchLeader Index 62.5 → 63.2.
19 Oct 2026 GPT-5.6 Terra (max): BenchLeader Index 63.8 → 64.4.
18 Oct 2026 Gemini 3.5 Flash (high): 3 new results (GDPval-AA v2.1, AA-Omniscience: accuracy, AA-Omniscience: non-hallucination).
18 Oct 2026 GPT-5.6 Terra (max): 5 new results (AutomationBench, GDP.pdf (AA), MLCR…).
16 Oct 2026 Gemini 3.5 Flash (high): 1 score revision.
16 Oct 2026 GPT-5.6 Terra (max): 1 new result (SREBench); 1 score revision.

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs