Is Gemini 3.8 Flash better than GPT-6 Astra?

GPT-6 Astra (max) leads on quality: 70.4 vs 64.4. The BenchLeader Index combines every independent quality benchmark; GPT-6 Astra (max) is ahead overall as of 2026-10-24, but check the category scores for your use.

Which is cheaper, Gemini 3.8 Flash or GPT-6 Astra, and will that change?

Gemini 3.8 Flash is cheaper today: $1.50 against $20.00 per million tokens, blended at three input tokens per output token. Yes, that changes: Gemini 3.8 Flash's list price changes on 1 Jan 2027, and from then Gemini 3.8 Flash is cheaper ($3.00 vs $20.00 blended).

Is Gemini 3.8 Flash better than GPT-6 Astra for coding?

GPT-6 Astra scores higher in coding (74 vs 64 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1585 for Gemini 3.8 Flash against 1775 for GPT-6 Astra.

Is Gemini 3.8 Flash better than GPT-6 Astra for agents and tool use?

GPT-6 Astra scores higher in agentic tasks (64 vs 51 on the category index, where 50 is average). On Terminal-Bench, the top shared agents & tools benchmark, it is 19.1% for Gemini 3.8 Flash against 58.2% for GPT-6 Astra.

Which is better for long documents?

They are level on long-context benchmarks (66 vs 65). Both take about 1.1M tokens: Gemini 3.8 Flash 1,048,576, GPT-6 Astra 1,050,000.

Which has lower latency?

Gemini 3.8 Flash (high) answers first: 25.1 s against 247.0 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 3.8 Flash or GPT-6 Astra?

Gemini 3.8 Flash streams faster: 141 against 58 output tokens per second.

When was Gemini 3.8 Flash released?

Gemini 3.8 Flash was released on 2 Sept 2026.

Gemini 3.8 Flash vs GPT-6 Astra

Full profiles: Gemini 3.8 Flash (Google) and GPT-6 Astra (OpenAI): every benchmark, price and rank.

Updated 23 Oct 2026 · Data from 10 sources

As of 24 Oct 2026, GPT-6 Astra (max) leads on quality (70.4 vs 64.4 on the BenchLeader Index), but Gemini 3.8 Flash (high) costs 13× less, so it is the better buy unless you need the extra quality. Gemini 3.8 Flash (high)'s current price runs until 31 Dec 2026; from 1 Jan 2027 Gemini 3.8 Flash (high) costs 6.7× less ($3.00 vs $20.00 per 1M blended); on use case, pick Gemini 3.8 Flash for human preference (69 vs 67), GPT-6 Astra for agents & tools (64 vs 51).

Gemini 3.8 Flash benchmarks high Google

GPT-6 Astra 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-6 Astra	74 vs 64 category score; Arena WebDev 1775 vs 1585	High
Agents & tool use	GPT-6 Astra	64 vs 51 category score; Terminal-Bench 58.2% vs 19.1%	High
Maths	GPT-6 Astra	72 vs 62 category score; FrontierMath Tiers 1–3 93.7% vs 68.4%	High
Reasoning	GPT-6 Astra	76 vs 68 category score; GPQA Diamond 95.8% vs 95.4%	High
Knowledge	GPT-6 Astra	80 vs 68 category score; SimpleQA Verified 75.6% vs 69.7%	High
Long documents	Either	66 vs 65 category score; AA-LCR 81.3% vs 80.7%	Either
Images and other media	Gemini 3.8 Flash	68 vs 66 category score; Arena Vision 1315 vs 1280	Medium
Chat quality (human preference)	Gemini 3.8 Flash	69 vs 67 on Arena votes	Medium
Lowest cost	Gemini 3.8 Flash	$1.50 vs $20.00 per 1M blended; agentic coding session $0.060 vs $0.800; from 1 Jan 2027: $3.00 vs $20.00	–
Fastest first answer	Gemini 3.8 Flash	25.1 s (Gemini 3.8 Flash (high)) vs 247.0 s (GPT-6 Astra (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

GPT-6 Astra (max) leads on quality: 70.4 vs 64.4.
Gemini 3.8 Flash (high) is stronger in human preference, long context, multimodal.
GPT-6 Astra (max) is stronger in agents & tools, coding, composite, knowledge, maths, reasoning.
Gemini 3.8 Flash (high) is 13× cheaper ($1.50 vs $20.00 per 1M blended) until 31 Dec 2026, then $3.00 vs $20.00 from 1 Jan 2027.
Gemini 3.8 Flash (high) streams 2.4× faster (141 vs 58 tokens per second).

At a glance

Spec	Gemini 3.8 Flash	GPT-6 Astra
Developer	Google	OpenAI
Released	2 Sept 2026	2 Sept 2026
Context window (tokens)	1,048,576	1,050,000
Compared at	Gemini 3.8 Flash (high)	GPT-6 Astra (max)
Open weights	No	No
Price in / out / cached input per 1M	$0.750 / $3.75 / $0.075	$10.00 / $50.00 / $1.00
Announced price change	$1.50 / $7.50 from 1 Jan 2027	None announced

Limits, availability and announced prices from the vendors' own pages: ai.google.dev pricing (checked 20 Oct 2026). Everything else is from the day's data.

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 3.8 Flash (high)	GPT-6 Astra (max)	Leader
Reasoning	68.2	76.2	GPT-6 Astra
Coding	63.5	74.0	GPT-6 Astra
Agents & tools	50.9	64.2	GPT-6 Astra
Maths	62.4	71.8	GPT-6 Astra
Knowledge	68.4	79.5	GPT-6 Astra
Human preference	69.1	66.7	Gemini 3.8 Flash
Multimodal	67.7	66.0	Gemini 3.8 Flash
Long context	65.7	65.4	level
Composite	75.3	88.4	GPT-6 Astra

Where sources disagree

Across the 91 benchmarks both have, Gemini 3.8 Flash leads 24, GPT-6 Astra leads 67. Independent sources split: Gemini 3.8 Flash leads on Arena Text; GPT-6 Astra leads on BenchLeader Index, AA Intelligence Index v4.3.2 and Vals Index.

Overall index	Gemini 3.8 Flash (high)	GPT-6 Astra (max)	Leader
BenchLeader Index	64.4	70.4	GPT-6 Astra
AA Intelligence Index v4.3.2	40.9	52.7	GPT-6 Astra
Vals Index	56.0	65.0	GPT-6 Astra
Arena Text	1496	1477	Gemini 3.8 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 3.8 Flash (high)	GPT-6 Astra (max)
Blended price per 1M tokens, until 31 Dec 2026	$1.50	$20.00
Input / output per 1M	$0.750 / $3.75	$10.00 / $50.00
Blended price per 1M from 1 Jan 2027	$3.00	$20.00
Input / output per 1M from 1 Jan 2027	$1.50 / $7.50	$10.00 / $50.00
Cached input per 1M	$0.075	$1.00
Price per task: chat reply	$0.0014	$0.019
Price per task: summarize a 30-page report	$0.011	$0.150
Price per task: code edit	$0.010	$0.135
Price per task: agentic coding session	$0.060	$0.800
Price per task: structured extraction	$0.0023	$0.030
Cost to run a full benchmark suite	$1.24	$3.26
Output speed	141 tok/s	58 tok/s
Time to first answer	25.1 s	247.0 s
Time to a complete answer	28.7 s	255.6 s

Per token is not per task: on Artificial Analysis' full suite Gemini 3.8 Flash (high) cost $1.24 and GPT-6 Astra (max) $3.26, because Gemini 3.8 Flash (high) used about 5.1× 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 3.8 Flash (high) scores 64.4 and takes 25 s to its first answer token; Gemini 3.8 Flash (medium) scores 64.4 in 3 s, Gemini 3.8 Flash (low) scores 61.0 in 3 s. GPT-6 Astra (max) scores 70.4 and takes 247 s to its first answer token; GPT-6 Astra (high) scores 69.6 in 35 s, GPT-6 Astra (xhigh) scores 68.9 in 130 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

144 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 3.8 Flash (high)	GPT-6 Astra (max)
BenchLeader Index	BenchLeader	64.4	70.4
Agents & tools score	BenchLeader	50.9	64.2
Coding score	BenchLeader	63.5	74.0
Composite score	BenchLeader	75.3	88.4
Human preference score	BenchLeader	69.1	66.7
Knowledge score	BenchLeader	68.4	79.5
Long context score	BenchLeader	65.7	65.4
Maths score	BenchLeader	62.4	71.8
Multimodal score	BenchLeader	67.7	66.0
Reasoning score	BenchLeader	68.2	76.2
Blended price $/M	BenchLeader	$1.50	$20.00
Output speed	BenchLeader	141 tok/s	58 tok/s
Time to first answer	BenchLeader	25.1 s	247.0 s
Context window	BenchLeader	1,048,576 tokens	1,050,000 tokens
Reasoning
GPQA Diamond	Epoch AI Benchmarking Hub	95.4%	95.8%
Humanity's Last Exam	Scale AI / CAIS	44.5%†	54.8%†
Arena Hard Prompts	Arena (LMArena)	1517	1501
LiveBench 2.0 Reasoning	LiveBench	89.3%†	92.7%†
LiveBench 1.0 Reasoning	LiveBench	89.3%	92.7%
GPQA Diamond (AA)	Artificial Analysis	95.3%	96.1%
Humanity's Last Exam (AA)	Artificial Analysis	47.8%	54.7%
GPQA Diamond (Vals)	Vals AI	94.4%	–
ARC-AGI-1	ARC Prize	98.5%	97.5%
ARC-AGI-2	ARC Prize	89.2%	95.0%
ARC-AGI-3	ARC Prize	35.0%	98.6%
CritPt	Artificial Analysis	18.3%	31.7%
MysteryMechanism	Vals AI	36.5%	53.1%
Chess Puzzles	Epoch AI Benchmarking Hub	58.0%	74.0%
Mystery Game Puzzles	Epoch AI Benchmarking Hub	47.0%	84.0%
LMCA	Epoch AI Benchmarking Hub	51.5%†	64.1%†
DTBench	Epoch AI Benchmarking Hub	95.7%†	97.1%†
BTF-3	Epoch AI Benchmarking Hub	–	13.5%†
Coding
SciCode	SciCode	56.6%	56.5%
WeirdML	WeirdML	84.8%	93.3%
FrontierCode	Cognition	41.2%†	53.3%
GSO-Bench	GSO-Bench	–	79.4%†
Arena Coding	Arena (LMArena)	1528	1543
Arena WebDev	Arena (LMArena)	1585	1775
LiveBench 2.0 Coding	LiveBench	82.2%†	93.7%†

Show all 144 benchmarks

Metric	Publisher	Gemini 3.8 Flash (high)	GPT-6 Astra (max)
Coding
LiveBench 1.0 Coding	LiveBench	72.5%	80.4%
LiveCodeBench	Vals AI	89.5%	–
IOI	Vals AI	56.9%	100.0%
SWE-bench (Vals)	Vals AI	80.0%	–
Code Migration	Vals AI	36.5%	67.7%
Code Migration v1.1	Vals AI	38.6%	80.6%
ProgramBench	Vals AI	1.0%	5.5%
SWE-bench Multimodal	Vals AI	40.8%	43.3%
Vibe Code Bench 1-100	Vals AI	18.8%	27.6%
Vibe Code Bench v1.1	Vals AI	78.7%	89.6%
SWE Atlas: Codebase QnA	Scale AI SEAL	47.0%†	59.1%†
SWE Atlas: Refactoring	Scale AI SEAL	44.8%†	59.0%†
SWE Atlas: Test Writing	Scale AI SEAL	53.7%†	50.7%†
MirrorCode	Epoch AI Benchmarking Hub	–	46.7%†
Surface Evolver Bench	Epoch AI Benchmarking Hub	76.9%	–
DeepSWE v1.1	Epoch AI Benchmarking Hub	73.8%	73.2%
CursorBench	Cursor	39.6%	–
ALE-Bench	Epoch AI Benchmarking Hub	1269.7	2951.3
FrontierSWE	Epoch AI Benchmarking Hub	19.6%	65.5%
Terminal-Bench 4.0 (AA)	Artificial Analysis	19.7%	59.1%
Terminal-Bench 2.1 (AA)	Artificial Analysis	87.6%	88.4%
Startrise Frontend	Startrise	64.6%†	79.9%†
FrontierCode 1.1 (AA)	Artificial Analysis	36.4%	47.0%
Agents & tools
Terminal-Bench	Terminal-Bench	19.1%	58.2%
Remote Labor Index	Scale AI / CAIS	5.8%†	20.8%†
APEX-Agents	Mercor	64.3%†	64.7%†
Arena Agent	Arena (LMArena)	3.6	14.7
LiveBench Long Agentic	LiveBench	30.1%†	82.4%†
LiveBench Browser	LiveBench	64.0%†	84.0%†
LiveBench Agentic Coding	LiveBench	54.2%	57.3%
Terminal-Bench 2.1 (Vals)	Vals AI	81.3%	87.3%
HiL-Bench	Scale AI SEAL	41.5%†	65.3%†
GDPval-AA v2.1	Artificial Analysis	46.8%	53.7%
τ³-Banking (AA)	Artificial Analysis	45.0%	41.4%
ITBench SRE (AA)	Artificial Analysis	52.5%	48.6%
Analyst Agent (AA)	Artificial Analysis	46.3%	51.3%
CUA-bench	Vals AI	4.2%	19.2%
CyberBench	Vals AI	43.8%	41.1%
Finance Agent v2	Vals AI	61.4%	53.5%
Finance Agent v2.1	Vals AI	65.8%	60.4%
Harvey's Legal Agent Benchmark v1.1	Vals AI	12.1%	7.1%
Harvey's Legal Agent Benchmark v1	Vals AI	10.0%	5.4%
Legal Research Bench	Vals AI	38.9%	39.4%
Robo-bench	Vals AI	–	23.3%
SkillsBench	Vals AI	58.0%	–
SREBench	Vals AI	11.1%	56.9%
Tax Agent Bench	Vals AI	32.1%	20.7%
Terminal-Bench 4.0 (Vals)	Vals AI	19.7%	59.6%
Terminal-Bench Science	Vals AI	8.6%	62.9%
Time Horizon Index: KSP	Vals AI	18.8%	90.5%
Arena Search	Arena (LMArena)	–	1246
BALROG	BALROG	–	68.3%
Vending-Bench 2	Andon Labs	5093.8†	15514.7†
AutomationBench	Artificial Analysis	59.9%	68.5%
GDP.pdf (AA)	Artificial Analysis	21.0%	31.0%
Harvey LAB-AA v1.1	Harvey	0.0%	8.6%
AA-Briefcase v1.1	Artificial Analysis	1202	1568
Terminal-Bench-Science 0.1 (AA)	Artificial Analysis	10.0%	63.3%
CWE-Bench (AA)	Artificial Analysis	52.5%	63.3%
DeepSec-Bench (AA)	Artificial Analysis	14.5%	36.9%
CyberGym end-to-end (AA)	Artificial Analysis	8.4%	0.0%
FACTS Search	Google	76.3%†	89.9%†
Maths
FrontierMath Tiers 1–3	Epoch AI Benchmarking Hub	68.4%	93.7%
FrontierMath Tier 4	Epoch AI Benchmarking Hub	21.9%	97.6%
OTIS Mock AIME	Epoch AI Benchmarking Hub	98.9%	100.0%
ProofBench	Vals AI	48.0%†	99.0%†
LiveBench Mathematics	LiveBench	91.6%	96.8%
Arena Maths	Arena (LMArena)	1526	1487
Knowledge
SimpleQA Verified	Epoch AI Benchmarking Hub	69.7%	75.6%
LiveBench 2.0 Data Analysis	LiveBench	54.0%†	83.0%†
LiveBench Research	LiveBench	79.1%†	85.2%†
LiveBench 1.0 Data Analysis	LiveBench	54.0%	83.0%
AA-Omniscience	Artificial Analysis	29.6	43.4
MMLU-Pro	Vals AI	90.2%	–
LegalBench	Vals AI	87.0%	–
TaxEval	Vals AI	74.5%	–
PRBench Finance	Scale AI SEAL	49.5%†	47.5%†
PRBench Legal	Scale AI SEAL	48.9%†	48.4%†
BioMysteryBench	Vals AI	62.2%	79.3%
Excel Modeling Benchmark	Vals AI	72.2%	71.7%
Excel Modeling Benchmark v1.1	Vals AI	72.9%	72.7%
MedCode	Vals AI	48.1%	48.5%
MedScribe	Vals AI	84.5%	87.9%
Public Benefits Bench v1.1	Vals AI	65.3%	–
DrugDiscoveryBench	Scale AI SEAL	–	68.7%
EBR-bench	Epoch AI Benchmarking Hub	–	76.2%
GDP.pdf	Epoch AI Benchmarking Hub	23.2%	34.2%
AA-Omniscience: accuracy	Artificial Analysis	54.6%	62.6%
AA-Omniscience: non-hallucination	Artificial Analysis	44.8%	48.7%
Instruction following
LiveBench Language	LiveBench	87.8%	89.4%
LiveBench Instruction Following	LiveBench	81.4%	75.6%
Arena Instruction Following	Arena (LMArena)	1490	1473
Human preference
Arena Text	Arena (LMArena)	1496	1477
Arena Creative Writing	Arena (LMArena)	1485	1450
Arena Multi-turn	Arena (LMArena)	1504	1485
Arena Longer Queries	Arena (LMArena)	1510	1489
Multimodal
Arena Vision	Arena (LMArena)	1315	1280
LiveBench Design	LiveBench	72.7%†	82.0%†
MMMU-Pro	Artificial Analysis	85.6%	86.9%
MMMU-Pro (Vals)	Vals AI	89.1%	–
MortgageTax	Vals AI	65.3%	–
SAGE	Vals AI	35.1%	46.4%
AudioMC	Scale AI SEAL	60.4%	–
AudioMC (text output)	Scale AI SEAL	60.4%	–
Blueprint-Bench 2	Epoch AI Benchmarking Hub	38.6%†	49.7%†
AA-3D	Artificial Analysis	969	1166
Long context
AA-LCR	Artificial Analysis	81.3%	80.7%
Arena Document	Arena (LMArena)	–	1473
MLCR	Artificial Analysis	10.6%	41.7%
Composite
Epoch Capabilities Index	Epoch AI Benchmarking Hub	157.4†	168.8†
LiveBench 2.0	LiveBench	67.3%†	86.1%†
LiveBench 1.0	LiveBench	75.8%	82.2%
AA Intelligence Index v4.3.2	Artificial Analysis	40.9	52.7
Vals Index	Vals AI	56.0	65.0
Vals Finance Index	Vals AI	60.5%	55.6%
Vals RSI Index	Vals AI	19.9%	27.1%
Vals Science Index	Vals AI	35.8%	65.1%
Vals Router Index	Vals AI	56.0%†	65.0%†
AA Cyber Index	Artificial Analysis	25.1	33.4

Data as of 2026-10-24. Best configuration of each model; every score links to its source on the model pages.

What changed

1 Jan 2027 Gemini 3.8 Flash: list price moves to $1.50 / $7.50 per 1M input / output tokens (announced).
23 Oct 2026 Gemini 3.8 Flash (high): 8 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
23 Oct 2026 GPT-6 Astra (max): 9 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
21 Oct 2026 Gemini 3.8 Flash (high): 1 score revision.
21 Oct 2026 GPT-6 Astra (max): 1 score revision.
20 Oct 2026 Gemini 3.8 Flash (high): 3 score revisions.
20 Oct 2026 GPT-6 Astra (max): 4 score revisions.
19 Oct 2026 Gemini 3.8 Flash (high): BenchLeader Index 63.7 → 64.5.
19 Oct 2026 GPT-6 Astra (max): BenchLeader Index 69.8 → 70.6.
17 Oct 2026 Gemini 3.8 Flash (high): 1 new result (AudioMC (text output)).

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