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Gemini 3.8 Flash vs GPT-6.1 Terra

Full profiles: Gemini 3.8 Flash (Google) and GPT-6.1 Terra (OpenAI): every benchmark, price and rank.

Updated · Data from 10 sources

As of 27 Oct 2026, Gemini 3.8 Flash (high) and GPT-6.1 Terra (max) are neck and neck on quality (64.3 vs 65.9 on the BenchLeader Index, inside the ±8.0 margin of error), and Gemini 3.8 Flash (high) costs 1.3× less, which makes it the better buy for most workloads. Gemini 3.8 Flash (high)'s current price runs until 31 Dec 2026; from 1 Jan 2027 GPT-6.1 Terra (max) costs 1.5× less ($2.00 vs $3.00 per 1M blended).

Gemini 3.8 Flash benchmarks high Google GPT-6.1 Terra benchmarks max OpenAIOpen 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 casePickWhyConfidence
ReasoningGPT-6.1 Terra86 vs 68 category score; CritPt 28.0% vs 18.3%High
KnowledgeGPT-6.1 Terra75 vs 68 category score; AA-Omniscience 29.8 vs 29.6Medium
Long documentsEither66 vs 66 category score; AA-LCR 81.3% vs 82.7%Either
Images and other mediaEither68 vs 68 category score; MMMU-Pro 85.6% vs 84.7%Either
Chat quality (human preference)–Only Gemini 3.8 Flash has an Arena rating (69 category score)Not comparable
Lowest costGemini 3.8 Flash (until 31 Dec 2026)$1.50 vs $2.00 per 1M blended; agentic coding session $0.060 vs $0.080; from 1 Jan 2027: $3.00 vs $2.00–
Fastest first answerGemini 3.8 Flash28.3 s (Gemini 3.8 Flash (high)) vs 131.8 s (GPT-6.1 Terra (max)) to the first answer token–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Gemini 3.8 Flash (high) and GPT-6.1 Terra (max) are neck and neck on quality (64.3 vs 65.9, within the ±8.0 margin).
  • Gemini 3.8 Flash (high) is stronger in agents & tools, coding, human preference, maths.
  • GPT-6.1 Terra (max) is stronger in composite, knowledge, long context, reasoning.
  • Gemini 3.8 Flash (high) is 1.3× cheaper ($1.50 vs $2.00 per 1M blended) until 31 Dec 2026, then $3.00 vs $2.00 from 1 Jan 2027.
  • Gemini 3.8 Flash (high) streams 1.5× faster (134 vs 91 tokens per second).

At a glance

SpecGemini 3.8 FlashGPT-6.1 Terra
DeveloperGoogleOpenAI
Released2 Sept 202626 Oct 2026
Context window (tokens)1,048,5761,050,000
Compared atGemini 3.8 Flash (high)GPT-6.1 Terra (max)
Open weightsNoNo
Price in / out / cached input per 1M$0.750 / $3.75 / $0.075$1.00 / $5.00 / $0.050
Announced price change$1.50 / $7.50 from 1 Jan 2027None 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.

CategoryGemini 3.8 Flash (high)GPT-6.1 Terra (max)Leader
Reasoning68.086.2GPT-6.1 Terra
Coding63.4–not comparable
Agents & tools51.3–not comparable
Maths62.4–not comparable
Knowledge68.374.5GPT-6.1 Terra
Human preference69.1–not comparable
Multimodal67.567.5level
Long context65.666.3level
Composite74.882.8GPT-6.1 Terra

Where sources disagree

Across the 14 benchmarks both have, Gemini 3.8 Flash leads 5, GPT-6.1 Terra leads 9. Every overall index that rates both puts GPT-6.1 Terra ahead.

Overall indexGemini 3.8 Flash (high)GPT-6.1 Terra (max)Leader
BenchLeader Index64.365.9neck and neck
AA Intelligence Index v4.3.240.948.1GPT-6.1 Terra

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.

MeasureGemini 3.8 Flash (high)GPT-6.1 Terra (max)
Blended price per 1M tokens, until 31 Dec 2026$1.50$2.00
Input / output per 1M$0.750 / $3.75$1.00 / $5.00
Blended price per 1M from 1 Jan 2027$3.00$2.00
Input / output per 1M from 1 Jan 2027$1.50 / $7.50$1.00 / $5.00
Cached input per 1M$0.075$0.050
Price per task: chat reply$0.0014$0.0019
Price per task: summarize a 30-page report$0.011$0.015
Price per task: code edit$0.010$0.013
Price per task: agentic coding session$0.060$0.080
Price per task: structured extraction$0.0023$0.0030
Cost to run a full benchmark suite$3.49$0.403
Output speed134 tok/s91 tok/s
Time to first answer28.3 s131.8 s
Time to a complete answer32.0 s137.3 s

Per token is not per task: on Artificial Analysis' full suite Gemini 3.8 Flash (high) cost $3.49 and GPT-6.1 Terra (max) $0.403, because Gemini 3.8 Flash (high) used about 11.5× 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 3.8 Flash (high) scores 64.3 and takes 28 s to its first answer token; Gemini 3.8 Flash (medium) scores 64.3 in 3 s, Gemini 3.8 Flash (low) scores 60.9 in 3 s. GPT-6.1 Terra (max) scores 65.9 and takes 132 s to its first answer token; GPT-6.1 Terra (xhigh) scores 65.0 in 18 s, GPT-6.1 Terra (high) scores 64.7 in 7 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

137 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.

MetricPublisherGemini 3.8 Flash (high)GPT-6.1 Terra (max)
BenchLeader IndexBenchLeader64.365.9
Agents & tools scoreBenchLeader51.3–
Coding scoreBenchLeader63.4–
Composite scoreBenchLeader74.882.8
Human preference scoreBenchLeader69.1–
Knowledge scoreBenchLeader68.374.5
Long context scoreBenchLeader65.666.3
Maths scoreBenchLeader62.4–
Multimodal scoreBenchLeader67.567.5
Reasoning scoreBenchLeader68.086.2
Blended price $/MBenchLeader$1.50$2.00
Output speedBenchLeader134 tok/s91 tok/s
Time to first answerBenchLeader28.3 s131.8 s
Context windowBenchLeader1,048,576 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub95.4%–
Humanity's Last ExamScale AI / CAIS44.5%†–
Arena Hard PromptsArena (LMArena)1517–
LiveBench 2.0 ReasoningLiveBench89.3%†88.7%†
LiveBench 1.0 ReasoningLiveBench89.3%–
GPQA Diamond (AA)Artificial Analysis95.3%–
Humanity's Last Exam (AA)Artificial Analysis47.8%46.3%
GPQA Diamond (Vals)Vals AI94.4%–
ARC-AGI-1ARC Prize98.5%–
ARC-AGI-2ARC Prize89.2%–
ARC-AGI-3ARC Prize35.0%–
CritPtArtificial Analysis18.3%28.0%
MysteryMechanismVals AI36.5%–
Chess PuzzlesEpoch AI Benchmarking Hub58.0%–
Mystery Game PuzzlesEpoch AI Benchmarking Hub47.0%–
LMCAEpoch AI Benchmarking Hub51.5%†–
DTBenchEpoch AI Benchmarking Hub95.7%†–
Coding
SciCodeSciCode56.6%–
WeirdMLWeirdML84.8%–
FrontierCodeCognition41.2%†–
Arena CodingArena (LMArena)1528–
Arena WebDevArena (LMArena)1585–
LiveBench 2.0 CodingLiveBench82.2%†90.8%†
LiveBench 1.0 CodingLiveBench72.5%–
SciCode (AA)Artificial Analysis56.6%55.1%
Show all 137 benchmarks
MetricPublisherGemini 3.8 Flash (high)GPT-6.1 Terra (max)
Coding
LiveCodeBenchVals AI89.5%–
IOIVals AI56.9%–
SWE-bench (Vals)Vals AI80.0%–
Code MigrationVals AI36.5%–
Code Migration v1.1Vals AI38.6%–
ProgramBenchVals AI1.0%–
SWE-bench MultimodalVals AI40.8%–
Vibe Code Bench 1-100Vals AI18.8%–
Vibe Code Bench v1.1Vals AI78.7%–
SWE Atlas: Codebase QnAScale AI SEAL47.0%†–
SWE Atlas: RefactoringScale AI SEAL44.8%†–
SWE Atlas: Test WritingScale AI SEAL53.7%†–
Surface Evolver BenchEpoch AI Benchmarking Hub76.9%–
DeepSWE v1.1Epoch AI Benchmarking Hub73.8%–
CursorBenchCursor39.6%–
ALE-BenchEpoch AI Benchmarking Hub1269.7–
FrontierSWEEpoch AI Benchmarking Hub19.6%–
Terminal-Bench 4.0 (AA)Artificial Analysis19.7%55.6%
Terminal-Bench 2.1 (AA)Artificial Analysis87.6%–
Startrise FrontendStartrise64.6%†–
FrontierCode 1.1 (AA)Artificial Analysis36.4%36.0%
Agents & tools
Terminal-BenchTerminal-Bench19.1%–
Remote Labor IndexScale AI / CAIS5.8%†–
APEX-AgentsMercor64.3%†–
Arena AgentArena (LMArena)3.2–
LiveBench Long AgenticLiveBench16.5%†48.6%†
LiveBench BrowserLiveBench45.1%†93.1%†
LiveBench Agentic CodingLiveBench54.2%–
Terminal-Bench 2.1 (Vals)Vals AI81.3%–
HiL-BenchScale AI SEAL41.5%†–
GDPval-AA v2.1Artificial Analysis46.8%–
τ³-Banking (AA)Artificial Analysis45.0%–
ITBench SRE (AA)Artificial Analysis52.5%–
Analyst Agent (AA)Artificial Analysis46.3%–
CUA-benchVals AI4.2%–
CyberBenchVals AI43.8%–
Finance Agent v2Vals AI61.4%–
Finance Agent v2.1Vals AI65.8%–
Harvey's Legal Agent Benchmark v1.1Vals AI12.1%–
Harvey's Legal Agent Benchmark v1Vals AI10.0%–
Legal Research BenchVals AI38.9%–
SkillsBenchVals AI58.0%–
SREBenchVals AI11.1%–
Tax Agent BenchVals AI32.1%–
Terminal-Bench 4.0 (Vals)Vals AI19.7%–
Terminal-Bench ScienceVals AI8.6%–
Time Horizon Index: KSPVals AI18.8%–
Vending-Bench 2Andon Labs5093.8†–
AutomationBenchArtificial Analysis59.9%60.2%
GDP.pdf (AA)Artificial Analysis21.0%28.6%
Harvey LAB-AA v1.1Harvey0.0%–
AA-Briefcase v1.1Artificial Analysis12021402
Terminal-Bench-Science 0.1 (AA)Artificial Analysis10.0%57.6%
CWE-Bench (AA)Artificial Analysis52.5%–
DeepSec-Bench (AA)Artificial Analysis14.5%–
CyberGym end-to-end (AA)Artificial Analysis8.4%–
FACTS SearchGoogle76.3%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub68.4%–
FrontierMath Tier 4Epoch AI Benchmarking Hub21.9%–
OTIS Mock AIMEEpoch AI Benchmarking Hub98.9%–
ProofBenchVals AI48.0%†–
LiveBench MathematicsLiveBench91.6%–
Arena MathsArena (LMArena)1526–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub69.7%–
LiveBench 2.0 Data AnalysisLiveBench54.0%†82.3%†
LiveBench ResearchLiveBench79.1%†73.9%†
LiveBench 1.0 Data AnalysisLiveBench54.0%–
AA-OmniscienceArtificial Analysis29.629.8
MMLU-ProVals AI90.2%–
LegalBenchVals AI87.0%–
TaxEvalVals AI74.5%–
PRBench FinanceScale AI SEAL49.5%†–
PRBench LegalScale AI SEAL48.9%†–
BioMysteryBenchVals AI62.2%–
Excel Modeling BenchmarkVals AI72.2%–
Excel Modeling Benchmark v1.1Vals AI72.9%–
MedCodeVals AI48.1%–
MedScribeVals AI84.5%–
Public Benefits Bench v1.1Vals AI65.3%–
GDP.pdfEpoch AI Benchmarking Hub23.2%–
AA-Omniscience: accuracyArtificial Analysis54.6%49.1%
AA-Omniscience: non-hallucinationArtificial Analysis44.8%62.0%
Instruction following
LiveBench LanguageLiveBench87.8%–
LiveBench Instruction FollowingLiveBench81.4%–
Arena Instruction FollowingArena (LMArena)1490–
Human preference
Arena TextArena (LMArena)1496–
Arena Creative WritingArena (LMArena)1485–
Arena Multi-turnArena (LMArena)1504–
Arena Longer QueriesArena (LMArena)1510–
Multimodal
Arena VisionArena (LMArena)1315–
LiveBench DesignLiveBench72.7%†82.3%†
MMMU-ProArtificial Analysis85.6%84.7%
MMMU-Pro (Vals)Vals AI89.1%–
MortgageTaxVals AI65.3%–
SAGEVals AI35.1%–
AudioMCScale AI SEAL60.4%–
AudioMC (text output)Scale AI SEAL60.4%–
Blueprint-Bench 2Epoch AI Benchmarking Hub38.6%†–
AA-3DArtificial Analysis966–
Long context
AA-LCRArtificial Analysis81.3%82.7%
MLCRArtificial Analysis10.6%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub157.4†–
LiveBench 2.0LiveBench59.2%†77.2%†
LiveBench 1.0LiveBench75.8%–
AA Intelligence Index v4.3.2Artificial Analysis40.948.1
Vals IndexVals AI56.0–
Vals Finance IndexVals AI60.5%–
Vals RSI IndexVals AI19.9%–
Vals Science IndexVals AI35.8%–
Vals Router IndexVals AI56.0%†–
AA Cyber IndexArtificial Analysis25.1–
Safety & honesty
FORTRESSScale AI SEAL–18.2%†

Data as of 2026-10-27. Best configuration of each model; every score links to its source on the model pages.

What changed

  • Gemini 3.8 Flash: list price moves to $1.50 / $7.50 per 1M input / output tokens (announced).
  • Gemini 3.8 Flash (high): cost per task moved from $1.24/M to $3.49/M (180% up).
  • Gemini 3.8 Flash (high): 8 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
  • Gemini 3.8 Flash (high): 1 score revision.
  • Gemini 3.8 Flash (high): 3 score revisions.
  • Gemini 3.8 Flash (high): BenchLeader Index 63.7 → 64.5.
  • Gemini 3.8 Flash (high): 1 new result (AudioMC (text output)).
  • Gemini 3.8 Flash (high): 1 new result (SREBench); 2 score revisions.
  • Gemini 3.8 Flash (high): 2 score revisions.
  • Gemini 3.8 Flash (high): 1 new result (Analyst Agent (AA)); 1 score revision.

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

Gemini 3.8 Flash vs GPT-6.1 Terra: questions

Is Gemini 3.8 Flash better than GPT-6.1 Terra?
Gemini 3.8 Flash (high) and GPT-6.1 Terra (max) are neck and neck on quality (64.3 vs 65.9, within the ±8.0 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-27, so check the category scores for your use.
Which is cheaper, Gemini 3.8 Flash or GPT-6.1 Terra, and will that change?
Gemini 3.8 Flash is cheaper today: $1.50 against $2.00 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 GPT-6.1 Terra is cheaper ($2.00 vs $3.00 blended).
Which is better for long documents?
They are level on long-context benchmarks (66 vs 66). Both take about 1.1M tokens: Gemini 3.8 Flash 1,048,576, GPT-6.1 Terra 1,050,000.
Which has lower latency?
Gemini 3.8 Flash (high) answers first: 28.3 s against 131.8 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-6.1 Terra?
Gemini 3.8 Flash streams faster: 134 against 91 output tokens per second.
Do independent benchmarks agree on Gemini 3.8 Flash vs GPT-6.1 Terra?
Across the 14 benchmarks both have, Gemini 3.8 Flash leads 5, GPT-6.1 Terra leads 9. Every overall index that rates both puts GPT-6.1 Terra ahead.
When was GPT-6.1 Terra released?
GPT-6.1 Terra was released on 26 Oct 2026.