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Model comparison

Gemini 3.5 Flash vs GPT-5.6 Luna

Data verified

Head-to-head evidence from 26 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

64.75/100
Margin
2.4pts
winning →
67.17/100
1 category wins4 category wins

Public leaderboard positions: Gemini 3.5 Flash #33 (Estimated); GPT-5.6 Luna #22 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. Gemini 3.5 Flash and GPT-5.6 Luna share 26 comparable benchmark results. 5 of 8 categories are comparable. 20 results are unique to Gemini 3.5 Flash; 15 to GPT-5.6 Luna.

Updated July 23, 2026
Shared results
26
Gemini 3.5 Flash only
20
GPT-5.6 Luna only
15
Comparable categories
5 / 8

Pick GPT-5.6 Luna if you want the stronger benchmark profile. Gemini 3.5 Flash only becomes the better choice if multimodal & grounded is the priority.

Confidence note. This is a partial-evidence comparison with 26 shared benchmark results across 6 evidence categories; 5 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

GPT-5.6 Luna has the cleaner BenchAlign overall profile here, landing at 67.17 versus 64.75. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

GPT-5.6 Luna's sharpest advantage is in knowledge, where it averages 92.3 against 47.2. The single biggest benchmark swing on the page is FrontierMath v2 (Tier 4), 14.583% to 58.500%. Gemini 3.5 Flash does hit back in multimodal & grounded, so the answer changes if that is the part of the workload you care about most.

Gemini 3.5 Flash is also the more expensive model on tokens at $1.50 input / $9.00 output per 1M tokens, versus $1.00 input / $6.00 output per 1M tokens for GPT-5.6 Luna.

Category breakdown

Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.

Category scores and score margins for Gemini 3.5 Flash and GPT-5.6 Luna
CategoryGemini 3.5 FlashΔGPT-5.6 Luna
KnowledgeGemini 3.5 Flash47.2Margin→ 45.1GPT-5.6 Luna92.3
MathGemini 3.5 Flash32.9Margin→ 40.7GPT-5.6 Luna73.6
CodingGemini 3.5 Flash53.9Margin→ 8.8GPT-5.6 Luna62.7
AgenticGemini 3.5 Flash77.2Margin→ 6.9GPT-5.6 Luna84.1
MultimodalGemini 3.5 Flash83.8Margin← 5.4GPT-5.6 Luna78.4
ReasoningGemini 3.5 Flash74.7MarginNo overlapGPT-5.6 LunaNot measured
Inst. FollowingGemini 3.5 Flash76.3MarginNo overlapGPT-5.6 LunaNot measured

Decisive benchmark drivers

The largest measured benchmark gaps in this matchup, with exact reported values.

More
A · Gemini 3.5 FlashB · GPT-5.6 Luna

  1. FrontierMath v2 (Tier 4)

    Math
    Source ↗
    A 14.583%B 58.500%
    Winner: GPT-5.6 LunaΔ 43.9
    FrontierMath v2 (Tier 4): Gemini 3.5 Flash scored 14.583%; GPT-5.6 Luna scored 58.500%. GPT-5.6 Luna wins this benchmark.

  2. FrontierMath v2 (Tiers 1-3)

    Math
    Source ↗
    A 38.966%B 78.600%
    Winner: GPT-5.6 LunaΔ 39.6
    FrontierMath v2 (Tiers 1-3): Gemini 3.5 Flash scored 38.966%; GPT-5.6 Luna scored 78.600%. GPT-5.6 Luna wins this benchmark.

  3. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 76.2%B 84.7%
    Winner: GPT-5.6 LunaΔ 8.5
    Terminal-Bench 2.0: Gemini 3.5 Flash scored 76.2%; GPT-5.6 Luna scored 84.7%. GPT-5.6 Luna wins this benchmark.

  4. SWE-bench Pro

    Coding
    Source ↗
    A 55.1%B 62.7%
    Winner: GPT-5.6 LunaΔ 7.6
    SWE-bench Pro: Gemini 3.5 Flash scored 55.1%; GPT-5.6 Luna scored 62.7%. GPT-5.6 Luna wins this benchmark.

  5. MMMU-Pro

    Multimodal
    Source ↗
    A 83.6%B 78.4%
    Winner: Gemini 3.5 FlashΔ 5.2
    MMMU-Pro: Gemini 3.5 Flash scored 83.6%; GPT-5.6 Luna scored 78.4%. Gemini 3.5 Flash wins this benchmark.

Operational comparison

Runtime and commercial metrics are compared only when both models have a complete sourced value.

MetricGemini 3.5 FlashGPT-5.6 LunaComparison
Input / output priceUSD per 1M tokensGemini 3.5 Flash$1.5 input / $9 outputGPT-5.6 Luna$1 input / $6 outputGPT-5.6 Luna has the lower combined listed price.
Generation speedtokens per secondGemini 3.5 Flash284.2 tok/sGPT-5.6 LunaNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenGemini 3.5 Flash18.55 sGPT-5.6 LunaNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensGemini 3.5 Flash1MGPT-5.6 Luna1MListed context windows are equal.

Benchmark Deep Dive

AgenticGPT-5.6 Luna wins
BenchmarkGemini 3.5 FlashGPT-5.6 LunaResult
Terminal-Bench 2.0Source 76.2%84.7%GPT-5.6 Luna leads
MCP AtlasSource 83.6%—Not comparable
ToolathlonSource 56.5%53.4%Gemini 3.5 Flash leads
OSWorld-VerifiedSource 78.4%—Not comparable
Finance Agent v2Source 57.9%—Not comparable
GDPval-AASource 13491584GPT-5.6 Luna leads
τ²-bench resultsSource 95.3%—Not comparable
GDPval-AASource 42.4%54.2%GPT-5.6 Luna leads
AA Agentic IndexSource 37.5%45.6%GPT-5.6 Luna leads
APEX-Agents-AASource 47.1%35.8%Gemini 3.5 Flash leads
Gert LabsSource 61.85%—Not comparable
ResearchClawBenchSource 18.0%—Not comparable
AA AutomationBenchSource 42.6%42.2%Gemini 3.5 Flash leads
AA EnterpriseOps-GymSource 50.1%—Not comparable
terminalBenchHardSource 40.9%—Not comparable
BrowseCompSource —83.3%Not comparable
OSWorld 2.0Source —45.6%Not comparable
CyberGymSource —77.9%Not comparable
ExploitGymSource —12.4%Not comparable
AA Harvey LABSource —87.9%Not comparable
AA ITBenchSource —40.3%Not comparable
AA Tau3 BankingSource —27.2%Not comparable
aaTerminalBench21Source —80.9%Not comparable
CodingGPT-5.6 Luna wins
BenchmarkGemini 3.5 FlashGPT-5.6 LunaResult
Terminal-Bench 2.0Source 76.2%84.7%GPT-5.6 Luna leads
SWE-bench ProSource 55.1%62.7%GPT-5.6 Luna leads
SciCodeSource 53.1%—Not comparable
Vibe Code BenchSource 48.68%—Not comparable
cursorBench31Source 49.8%—Not comparable
cursorBench32Source 48.8%61.1%GPT-5.6 Luna leads
AA Coding IndexSource 70.1%71.5%GPT-5.6 Luna leads
AA-SciCodeSource 53.1%52.5%Gemini 3.5 Flash leads
deepSweSource —67.2%Not comparable
FrontierCode 1.1 ExtendedSource —55.1%Not comparable
Reasoning
BenchmarkGemini 3.5 FlashGPT-5.6 LunaResult
MRCRv2Source 77.3%—Not comparable
MRCR 1MSource 26.6%—Not comparable
ARC-AGI-2Source 72.1%—Not comparable
AA-LCRSource 69.3%74.0%GPT-5.6 Luna leads
CritPtSource 13.1%20.6%GPT-5.6 Luna leads
ARC-AGI-3Source —0.2%Not comparable
KnowledgeGPT-5.6 Luna wins
BenchmarkGemini 3.5 FlashGPT-5.6 LunaResult
Artificial Analysis Intelligence IndexSource 50.2%51.2%GPT-5.6 Luna leads
GPQASource 92.2%92.3%GPT-5.6 Luna leads
GPQA-DSource 92.7%92.3%Gemini 3.5 Flash leads
HLESource 40.2%—Not comparable
AA-Omniscience AccuracySource 51.9%41.5%Gemini 3.5 Flash leads
AA-Omniscience Hallucination RateSource 60.7%90.1%Gemini 3.5 Flash leads
AA-GPQA DiamondSource 92.2%91.1%Gemini 3.5 Flash leads
AA-HLESource 41.0%37.2%Gemini 3.5 Flash leads
AA-Omniscience IndexSource 22.7%-11.2%Gemini 3.5 Flash leads
HealthBench ProfessionalSource —55.7%Not comparable
HealthBench HardSource —32.0%Not comparable
MathGPT-5.6 Luna wins
BenchmarkGemini 3.5 FlashGPT-5.6 LunaResult
FrontierMath v2 (Tiers 1-3)Source 38.966%78.600%GPT-5.6 Luna leads
FrontierMath v2 (Tier 4)Source 14.583%58.500%GPT-5.6 Luna leads
FrontierMath (legacy)Source —78.6%Not comparable
MultimodalGemini 3.5 Flash wins
BenchmarkGemini 3.5 FlashGPT-5.6 LunaResult
CharXivSource 84.2%—Not comparable
MMMU-ProSource 83.6%78.4%Gemini 3.5 Flash leads
Blueprint-Bench 2Source 33.6%—Not comparable
AA-MMMU-ProSource 84.3%78.6%Gemini 3.5 Flash leads
Design Arena WebsiteSource 1285—Not comparable
MMMU-Pro w/ PythonSource —79.5%Not comparable
Inst. Following
BenchmarkGemini 3.5 FlashGPT-5.6 LunaResult
IFBenchSource 76.3%—Not comparable
AA-IFBenchSource 76.3%—Not comparable
Frequently Asked Questions (6)

Which is better, Gemini 3.5 Flash or GPT-5.6 Luna?

GPT-5.6 Luna is ahead on BenchLM's BenchAlign leaderboard, 67.17 to 64.75. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 14.583% and 58.500%.

Which is better for knowledge tasks, Gemini 3.5 Flash or GPT-5.6 Luna?

GPT-5.6 Luna has the edge for knowledge tasks in this comparison, averaging 92.3 versus 47.2. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.

Which is better for coding, Gemini 3.5 Flash or GPT-5.6 Luna?

GPT-5.6 Luna has the edge for coding in this comparison, averaging 62.7 versus 53.9. Inside this category, cursorBench32 is the benchmark that creates the most daylight between them.

Which is better for math, Gemini 3.5 Flash or GPT-5.6 Luna?

GPT-5.6 Luna has the edge for math in this comparison, averaging 73.6 versus 32.9. Inside this category, FrontierMath v2 (Tier 4) is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, Gemini 3.5 Flash or GPT-5.6 Luna?

GPT-5.6 Luna has the edge for agentic tasks in this comparison, averaging 84.1 versus 77.2. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.

Which is better for multimodal and grounded tasks, Gemini 3.5 Flash or GPT-5.6 Luna?

Gemini 3.5 Flash has the edge for multimodal and grounded tasks in this comparison, averaging 83.8 versus 78.4. Inside this category, AA-MMMU-Pro is the benchmark that creates the most daylight between them.

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