BenchLeader

Gemini 3.8 Flash vs GPT-5.4

Full profiles: Gemini 3.8 Flash (Google) and GPT-5.4 (OpenAI): every benchmark, price and rank.

Updated · Data from 12 sources

As of 24 Oct 2026, Gemini 3.8 Flash (high) and GPT-5.4 (xhigh) are neck and neck on quality (64.4 vs 64.7 on the BenchLeader Index, inside the ±4.7 margin of error), and Gemini 3.8 Flash (high) costs 3.8× 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 Gemini 3.8 Flash (high) costs 1.9× less ($3.00 vs $5.63 per 1M blended); on use case, pick Gemini 3.8 Flash for knowledge (68 vs 60), GPT-5.4 for agents & tools (64 vs 51).

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
CodingGPT-5.465 vs 64 category score; LiveCodeBench 84.1% vs 89.5%Medium
Agents & tool useGPT-5.464 vs 51 category score; τ³-Banking (AA) 39.6% vs 45.0%High
MathsGPT-5.465 vs 62 category score; FrontierMath Tiers 1–3 78.6% vs 68.4%Medium
ReasoningEither68 vs 69 category score; GPQA Diamond 95.4% vs 93.3%Either
KnowledgeGemini 3.8 Flash68 vs 60 category score; SimpleQA Verified 69.7% vs 45.1%High
Long documentsEither66 vs 66 category score; AA-LCR 81.3% vs 82.0%Either
Images and other mediaGemini 3.8 Flash68 vs 61 category score; MMMU-Pro 85.6% vs 78.4%Medium
Chat quality (human preference)–Only Gemini 3.8 Flash has an Arena rating (69 category score)Not comparable
Lowest costGemini 3.8 Flash$1.50 vs $5.63 per 1M blended; agentic coding session $0.060 vs $0.210; from 1 Jan 2027: $3.00 vs $5.63–
Fastest first answerGemini 3.8 Flash25.1 s (Gemini 3.8 Flash (high)) vs 110.0 s (GPT-5.4 (xhigh)) 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-5.4 (xhigh) are neck and neck on quality (64.4 vs 64.7, within the ±4.7 margin).
  • Gemini 3.8 Flash (high) is stronger in composite, human preference, knowledge, multimodal.
  • GPT-5.4 (xhigh) is stronger in agents & tools, coding, long context, maths, reasoning, instruction following.
  • Gemini 3.8 Flash (high) is 3.8× cheaper ($1.50 vs $5.63 per 1M blended) until 31 Dec 2026, then $3.00 vs $5.63 from 1 Jan 2027.
  • Gemini 3.8 Flash (high) streams 1.5× faster (141 vs 96 tokens per second).

At a glance

SpecGemini 3.8 FlashGPT-5.4
DeveloperGoogleOpenAI
Released2 Sept 20265 Mar 2026
Context window (tokens)1,048,5761,050,000
Compared atGemini 3.8 Flash (high)GPT-5.4 (xhigh)
Open weightsNoNo
Price in / out / cached input per 1M$0.750 / $3.75 / $0.075$2.50 / $15.00 / $0.250
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-5.4 (xhigh)Leader
Reasoning68.269.1level
Coding63.564.6GPT-5.4
Agents & tools50.963.6GPT-5.4
Maths62.465.2GPT-5.4
Knowledge68.459.7Gemini 3.8 Flash
Instruction following–72.3not comparable
Human preference69.1–not comparable
Multimodal67.761.4Gemini 3.8 Flash
Long context65.766.1level
Composite75.373.1Gemini 3.8 Flash

Where sources disagree

Across the 47 benchmarks both have, Gemini 3.8 Flash leads 36, GPT-5.4 leads 10 and 1 is a tie. Every overall index that rates both puts Gemini 3.8 Flash ahead.

Overall indexGemini 3.8 Flash (high)GPT-5.4 (xhigh)Leader
BenchLeader Index64.464.7neck and neck
AA Intelligence Index v4.3.240.939.0Gemini 3.8 Flash
Arena Text14961475†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.

MeasureGemini 3.8 Flash (high)GPT-5.4 (xhigh)
Blended price per 1M tokens, until 31 Dec 2026$1.50$5.63
Input / output per 1M$0.750 / $3.75$2.50 / $15.00
Blended price per 1M from 1 Jan 2027$3.00$5.63
Input / output per 1M from 1 Jan 2027$1.50 / $7.50$2.50 / $15.00
Cached input per 1M$0.075$0.250
Price per task: chat reply$0.0014$0.0055
Price per task: summarize a 30-page report$0.011$0.039
Price per task: code edit$0.010$0.037
Price per task: agentic coding session$0.060$0.210
Price per task: structured extraction$0.0023$0.0080
Cost to run a full benchmark suite$1.24–
Output speed141 tok/s96 tok/s
Time to first answer25.1 s110.0 s
Time to a complete answer28.7 s115.2 s

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-5.4 (xhigh) scores 64.7 and takes 110 s to its first answer token; GPT-5.4 (low) scores 59.7 in 2 s, GPT-5.4 scores 58.2 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

173 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-5.4 (xhigh)
BenchLeader IndexBenchLeader64.464.7
Agents & tools scoreBenchLeader50.963.6
Coding scoreBenchLeader63.564.6
Composite scoreBenchLeader75.373.1
Human preference scoreBenchLeader69.1–
Knowledge scoreBenchLeader68.459.7
Long context scoreBenchLeader65.766.1
Maths scoreBenchLeader62.465.2
Multimodal scoreBenchLeader67.761.4
Reasoning scoreBenchLeader68.269.1
Instruction following scoreBenchLeader–72.3
Blended price $/MBenchLeader$1.50$5.63
Output speedBenchLeader141 tok/s96 tok/s
Time to first answerBenchLeader25.1 s110.0 s
Context windowBenchLeader1,048,576 tokens1,050,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub95.4%93.3%
Humanity's Last ExamScale AI / CAIS44.5%†36.2%
Arena Hard PromptsArena (LMArena)15171487†
LiveBench 2.0 ReasoningLiveBench89.3%†–
LiveBench 1.0 ReasoningLiveBench89.3%88.1%
GPQA Diamond (AA)Artificial Analysis95.3%92.0%
Humanity's Last Exam (AA)Artificial Analysis47.8%43.7%
GPQA Diamond (Vals)Vals AI94.4%91.7%
Kagi LLM BenchmarkKagi LLM Benchmark–63.8%†
ARC-AGI-1ARC Prize98.5%93.7%
ARC-AGI-2ARC Prize89.2%74.0%
ARC-AGI-3ARC Prize35.0%0.2%†
CritPtArtificial Analysis18.3%23.4%
MysteryMechanismVals AI36.5%–
Chess PuzzlesEpoch AI Benchmarking Hub58.0%48.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub47.0%37.0%
CL-benchEpoch AI Benchmarking Hub–27.9%
CL-bench LifeEpoch AI Benchmarking Hub–21.7%
LMCAEpoch AI Benchmarking Hub51.5%†52.0%
DTBenchEpoch AI Benchmarking Hub95.7%†94.4%
ForecastBenchForecastBench–63.1%†
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub–76.9%†
SciCodeSciCode56.6%56.6%
WeirdMLWeirdML84.8%77.7%
FrontierCodeCognition41.2%†–
Show all 173 benchmarks
MetricPublisherGemini 3.8 Flash (high)GPT-5.4 (xhigh)
Coding
GSO-BenchGSO-Bench–31.4%
Arena CodingArena (LMArena)15281511†
Arena WebDevArena (LMArena)15851400†
LiveBench 2.0 CodingLiveBench82.2%†–
LiveBench 1.0 CodingLiveBench72.5%77.5%
SciCode (AA)Artificial Analysis56.6%–
LiveCodeBenchVals AI89.5%84.1%
IOIVals AI56.9%–
SWE-bench (Vals)Vals AI80.0%78.2%
SWE-Bench ProScale AI SEAL–59.1%
Code MigrationVals AI36.5%35.0%
Code Migration v1.1Vals AI38.6%–
ProgramBenchVals AI1.0%0.0%
SWE-bench MultimodalVals AI40.8%–
Vibe Code Bench 1-100Vals AI18.8%–
Vibe Code Bench v1.1Vals AI78.7%67.4%
SWE-Bench Pro (private)Scale AI SEAL–59.1%
SWE Atlas: Codebase QnAScale AI SEAL47.0%†40.8%
SWE Atlas: RefactoringScale AI SEAL44.8%†44.3%
SWE Atlas: Test WritingScale AI SEAL53.7%†44.4%
MirrorCodeEpoch AI Benchmarking Hub–15.6%†
Surface Evolver BenchEpoch AI Benchmarking Hub76.9%–
DeepSWE v1.1Epoch AI Benchmarking Hub73.8%51.8%
CursorBenchCursor39.6%–
ALE-BenchEpoch AI Benchmarking Hub1269.71607†
AlgoTuneAlgoTune–1.9†
FrontierSWEEpoch AI Benchmarking Hub19.6%–
Terminal-Bench 4.0 (AA)Artificial Analysis19.7%–
Terminal-Bench 2.1 (AA)Artificial Analysis87.6%78.3%
Startrise FrontendStartrise64.6%†–
FrontierCode 1.1 (AA)Artificial Analysis36.4%–
Agents & tools
Terminal-BenchTerminal-Bench19.1%81.8%†
Remote Labor IndexScale AI / CAIS5.8%†–
APEX-AgentsMercor64.3%†52.4%†
Arena AgentArena (LMArena)3.61.4†
LiveBench Long AgenticLiveBench30.1%†–
LiveBench BrowserLiveBench64.0%†–
LiveBench Agentic CodingLiveBench54.2%53.8%
Terminal-Bench HardArtificial Analysis–57.6%
τ²-Bench Telecom (AA)Artificial Analysis–87.1%
Terminal-Bench 2.1 (Vals)Vals AI81.3%–
MCP AtlasScale AI SEAL–70.6%
HiL-BenchScale AI SEAL41.5%†9.7%†
τ³-bench Bankingτ²-bench–39.4%
GDPval-AA v2.1Artificial Analysis46.8%–
τ³-Banking (AA)Artificial Analysis45.0%39.6%
ITBench SRE (AA)Artificial Analysis52.5%–
Analyst Agent (AA)Artificial Analysis46.3%–
APEX-Agents (AA)Artificial Analysis–33.3%
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%0.0%
Legal Research BenchVals AI38.9%–
SkillsBenchVals AI58.0%51.7%
SREBenchVals AI11.1%–
Tax Agent BenchVals AI32.1%–
Terminal-Bench 2.0 (Vals)Vals AI–58.4%†
Terminal-Bench 4.0 (Vals)Vals AI19.7%–
Terminal-Bench ScienceVals AI8.6%–
Time Horizon Index: KSPVals AI18.8%–
DeepResearch BenchDeepResearch Bench–35.1%†
PostTrainBenchEpoch AI Benchmarking Hub–19.0%†
METR Time HorizonsMETR–74.3%
GBAEvalEpoch AI Benchmarking Hub–45.1%†
Vending-Bench 2Andon Labs5093.8†6144.2†
AutomationBenchArtificial Analysis59.9%–
GDP.pdf (AA)Artificial Analysis21.0%–
Harvey LAB-AA v1.1Harvey0.0%–
AA-Briefcase v1.1Artificial Analysis1202–
Terminal-Bench-Science 0.1 (AA)Artificial Analysis10.0%–
CWE-Bench (AA)Artificial Analysis52.5%–
DeepSec-Bench (AA)Artificial Analysis14.5%–
CyberGym end-to-end (AA)Artificial Analysis8.4%–
DeepSearchQAGoogle–63.7%†
FACTS SearchGoogle76.3%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub68.4%78.6%
FrontierMath Tier 4Epoch AI Benchmarking Hub21.9%49.0%
OTIS Mock AIMEEpoch AI Benchmarking Hub98.9%95.3%
ProofBenchVals AI48.0%†56.0%
LiveBench MathematicsLiveBench91.6%94.2%
AIME (Vals)Vals AI–96.7%
AIME 2026MathArena–99.2%
HMMT February 2026MathArena–97.7%
USAMO 2026MathArena–95.2%
MathArena ApexMathArena–54.2%
Arena MathsArena (LMArena)15261460†
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub69.7%45.1%
LiveBench 2.0 Data AnalysisLiveBench54.0%†–
LiveBench ResearchLiveBench79.1%†–
LiveBench 1.0 Data AnalysisLiveBench54.0%79.3%
AA-OmniscienceArtificial Analysis29.65.8
MMLU-ProVals AI90.2%87.5%
LegalBenchVals AI87.0%86.0%
CorpFinVals AI–65.3%
TaxEvalVals AI74.5%74.0%
MedQAVals AI–96.1%
PRBench FinanceScale AI SEAL49.5%†45.6%†
PRBench LegalScale AI SEAL48.9%†44.4%†
MultiNRCScale AI SEAL–58.3%†
BioMysteryBenchVals AI62.2%–
CaseLaw v2Vals AI–63.8%
Excel Modeling BenchmarkVals AI72.2%–
Excel Modeling Benchmark v1.1Vals AI72.9%–
MedCodeVals AI48.1%41.3%
MedScribeVals AI84.5%77.5%
Public Benefits Bench v1.1Vals AI65.3%–
EBR-benchEpoch AI Benchmarking Hub–25.4%
GDP.pdfEpoch AI Benchmarking Hub23.2%–
AA-Omniscience: accuracyArtificial Analysis54.6%50.9%
AA-Omniscience: non-hallucinationArtificial Analysis44.8%8.3%
Instruction following
LiveBench LanguageLiveBench87.8%82.6%
LiveBench Instruction FollowingLiveBench81.4%70.2%
IFBenchArtificial Analysis–74.0%
Arena Instruction FollowingArena (LMArena)14901460†
Human preference
Arena TextArena (LMArena)14961465†
EQ-Bench 4EQ-Bench–1272†
Arena Creative WritingArena (LMArena)14851435†
Arena Multi-turnArena (LMArena)15041480†
Arena Longer QueriesArena (LMArena)15101477†
Multimodal
Arena VisionArena (LMArena)13151292†
LiveBench DesignLiveBench72.7%†–
MMMU-ProArtificial Analysis85.6%78.4%
VISTAScale AI SEAL–50.9%†
MMMU-Pro (Vals)Vals AI89.1%87.5%
MortgageTaxVals AI65.3%68.3%
SAGEVals AI35.1%43.3%
AudioMCScale AI SEAL60.4%–
AudioMC (text output)Scale AI SEAL60.4%–
VTBScale AI SEAL–29.2%†
Blueprint-Bench 2Epoch AI Benchmarking Hub38.6%†27.1%†
AA-3DArtificial Analysis969–
Long context
AA-LCRArtificial Analysis81.3%82.0%
Arena DocumentArena (LMArena)–1470†
MLCRArtificial Analysis10.6%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub157.4†157.3†
LiveBench 2.0LiveBench67.3%†–
LiveBench 1.0LiveBench75.8%78.0%
AA Intelligence Index v4.3.2Artificial Analysis40.939.0
Vals IndexVals AI56.0–
Vals Finance IndexVals AI60.5%–
Vals RSI IndexVals AI19.9%15.5%
Vals Science IndexVals AI35.8%–
Vals Router IndexVals AI56.0%†–
AA Cyber IndexArtificial Analysis25.1–
Safety & honesty
MASKScale AI SEAL–89.7%†

Data as of 2026-10-24. 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): 8 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
  • GPT-5.4 (xhigh): 2 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index).
  • 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.
  • GPT-5.4 (xhigh): 2 new results (USAMO 2026, τ³-bench Banking).
  • 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.

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

Gemini 3.8 Flash vs GPT-5.4: questions

Is Gemini 3.8 Flash better than GPT-5.4?
Gemini 3.8 Flash (high) and GPT-5.4 (xhigh) are neck and neck on quality (64.4 vs 64.7, within the ±4.7 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-24, so check the category scores for your use.
Which is cheaper, Gemini 3.8 Flash or GPT-5.4, and will that change?
Gemini 3.8 Flash is cheaper today: $1.50 against $5.63 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 $5.63 blended).
Is Gemini 3.8 Flash better than GPT-5.4 for coding?
GPT-5.4 scores higher in coding (65 vs 64 on the category index, where 50 is average). On LiveCodeBench, the top shared coding benchmark, it is 89.5% for Gemini 3.8 Flash against 84.1% for GPT-5.4.
Is Gemini 3.8 Flash better than GPT-5.4 for agents and tool use?
GPT-5.4 scores higher in agentic tasks (64 vs 51 on the category index, where 50 is average). On τ³-Banking (AA), the top shared agents & tools benchmark, it is 45.0% for Gemini 3.8 Flash against 39.6% for GPT-5.4.
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-5.4 1,050,000.
Which has lower latency?
Gemini 3.8 Flash (high) answers first: 25.1 s against 110.0 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-5.4?
Gemini 3.8 Flash streams faster: 141 against 96 output tokens per second.
Do independent benchmarks agree on Gemini 3.8 Flash vs GPT-5.4?
Across the 47 benchmarks both have, Gemini 3.8 Flash leads 36, GPT-5.4 leads 10 and 1 is a tie. Every overall index that rates both puts Gemini 3.8 Flash ahead.
When was Gemini 3.8 Flash released?
Gemini 3.8 Flash was released on 2 Sept 2026.