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Model comparison

DeepSeek V4 Flash (Max) vs Gemini 2.5 Pro

Data verified

Head-to-head evidence from 19 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

N/A
No comparison
57.25/100
3 category wins0 category wins

Public leaderboard positions: DeepSeek V4 Flash (Max) unranked (Not scored); Gemini 2.5 Pro #70 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V4 Flash (Max) and Gemini 2.5 Pro share 19 comparable benchmark results. 3 of 8 categories are comparable. 26 results are unique to DeepSeek V4 Flash (Max); 5 to Gemini 2.5 Pro.

Updated July 23, 2026
Shared results
19
DeepSeek V4 Flash (Max) only
26
Gemini 2.5 Pro only
5
Comparable categories
3 / 8

Treat this as a split decision. DeepSeek V4 Flash (Max) makes more sense if mathematics is the priority or you want the cheaper token bill; Gemini 2.5 Pro is the better fit if you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 19 shared benchmark results across 6 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

DeepSeek V4 Flash (Max) and Gemini 2.5 Pro finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.

Gemini 2.5 Pro is also the more expensive model on tokens at $1.25 input / $10.00 output per 1M tokens, versus $0.14 input / $0.28 output per 1M tokens for DeepSeek V4 Flash (Max). That is roughly 35.7x on output cost alone. DeepSeek V4 Flash (Max) is the reasoning model in the pair, while Gemini 2.5 Pro is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use.

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 DeepSeek V4 Flash (Max) and Gemini 2.5 Pro
CategoryDeepSeek V4 Flash (Max)ΔGemini 2.5 Pro
MathDeepSeek V4 Flash (Max)94.8Margin← 83.2Gemini 2.5 Pro11.6
KnowledgeDeepSeek V4 Flash (Max)55.3Margin← 27.9Gemini 2.5 Pro27.4
CodingDeepSeek V4 Flash (Max)68.8Margin← 5.0Gemini 2.5 Pro63.8
AgenticDeepSeek V4 Flash (Max)63.8MarginNo overlapGemini 2.5 ProNot measured

Decisive benchmark drivers

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

More
A · DeepSeek V4 Flash (Max)B · Gemini 2.5 Pro

  1. HLE

    Knowledge
    Source ↗
    A 34.8%B 18.8%
    Winner: DeepSeek V4 Flash (Max)Δ 16
    HLE: DeepSeek V4 Flash (Max) scored 34.8%; Gemini 2.5 Pro scored 18.8%. DeepSeek V4 Flash (Max) wins this benchmark.

  2. SWE-bench Verified

    Coding
    Source ↗
    A 79%B 63.8%
    Winner: DeepSeek V4 Flash (Max)Δ 15.2
    SWE-bench Verified: DeepSeek V4 Flash (Max) scored 79%; Gemini 2.5 Pro scored 63.8%. DeepSeek V4 Flash (Max) wins this benchmark.

  3. GPQA

    Knowledge
    Source ↗
    A 88.1%B 83%
    Winner: DeepSeek V4 Flash (Max)Δ 5.1
    GPQA: DeepSeek V4 Flash (Max) scored 88.1%; Gemini 2.5 Pro scored 83%. DeepSeek V4 Flash (Max) wins this benchmark.

Operational comparison

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

MetricDeepSeek V4 Flash (Max)Gemini 2.5 ProComparison
Input / output priceUSD per 1M tokensDeepSeek V4 Flash (Max)$0.14 input / $0.28 outputGemini 2.5 Pro$1.25 input / $10 outputDeepSeek V4 Flash (Max) has the lower combined listed price.
Generation speedtokens per secondDeepSeek V4 Flash (Max)Not availableGemini 2.5 Pro117 tok/sA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V4 Flash (Max)Not availableGemini 2.5 Pro21.19 sA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V4 Flash (Max)1MGemini 2.5 Pro1MListed context windows are equal.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V4 Flash (Max)Gemini 2.5 ProResult
Terminal-Bench 2.0Source 56.9%—Not comparable
BrowseCompSource 73.2%—Not comparable
HLE w/ toolsSource 45.1%—Not comparable
MCP AtlasSource 69%—Not comparable
GDPval-AASource 1189665DeepSeek V4 Flash (Max) leads
ToolathlonSource 47.8%—Not comparable
AA Agentic IndexSource 31.1%7.1%DeepSeek V4 Flash (Max) leads
τ²-bench resultsSource 95%54.1%DeepSeek V4 Flash (Max) leads
GDPval-AASource 34.4%8.3%DeepSeek V4 Flash (Max) leads
AA BriefcaseSource 831—Not comparable
AA EnterpriseOps-GymSource 39.6%—Not comparable
AA Harvey LABSource 81.3%—Not comparable
AA ITBenchSource 31.5%—Not comparable
AA Tau3 BankingSource 22.9%—Not comparable
terminalBenchHardSource 35.6%—Not comparable
Gert LabsSource —42.01%Not comparable
CodingDeepSeek V4 Flash (Max) wins
BenchmarkDeepSeek V4 Flash (Max)Gemini 2.5 ProResult
CodeforcesSource 3052.0—Not comparable
SWE-bench VerifiedSource 79%63.8%DeepSeek V4 Flash (Max) leads
SWE-bench ProSource 52.6%—Not comparable
SWE MultilingualSource 73.3%—Not comparable
Terminal-Bench 2.0Source 56.9%—Not comparable
AA Coding IndexSource 56.2%33.3%DeepSeek V4 Flash (Max) leads
AA-SciCodeSource 44.9%42.8%DeepSeek V4 Flash (Max) leads
Vibe Code BenchSource —0.40%Not comparable
Reasoning
BenchmarkDeepSeek V4 Flash (Max)Gemini 2.5 ProResult
MRCR 1MSource 78.7%—Not comparable
CorpusQA 1MSource 60.5%—Not comparable
AA-LCRSource 63.0%66.0%Gemini 2.5 Pro leads
CritPtSource 7.1%2.6%DeepSeek V4 Flash (Max) leads
KnowledgeDeepSeek V4 Flash (Max) wins
BenchmarkDeepSeek V4 Flash (Max)Gemini 2.5 ProResult
MMLU-ProSource 86.2%—Not comparable
SimpleQASource 34.1%—Not comparable
Chinese-SimpleQASource 78.9%—Not comparable
GPQASource 88.1%83%DeepSeek V4 Flash (Max) leads
GPQA-DSource 88.1%—Not comparable
HLESource 34.8%18.8%DeepSeek V4 Flash (Max) leads
Artificial Analysis Intelligence IndexSource 40.3%25.8%DeepSeek V4 Flash (Max) leads
AA-GPQA DiamondSource 89.4%84.4%DeepSeek V4 Flash (Max) leads
AA-HLESource 32.1%21.1%DeepSeek V4 Flash (Max) leads
AA-Omniscience IndexSource -22.9%-14.3%Gemini 2.5 Pro leads
AA-Omniscience AccuracySource 37.2%39.0%Gemini 2.5 Pro leads
AA-Omniscience Hallucination RateSource 95.8%87.4%Gemini 2.5 Pro leads
AA Openness IndexSource 50.0%—Not comparable
MathDeepSeek V4 Flash (Max) wins
BenchmarkDeepSeek V4 Flash (Max)Gemini 2.5 ProResult
HMMT Feb 2026Source 94.8%—Not comparable
IMOAnswerBenchSource 88.4%—Not comparable
ApexSource 33.0%—Not comparable
Apex ShortlistSource 85.7%—Not comparable
FrontierMath v2 (Tiers 1-3)Source —14.138%Not comparable
FrontierMath v2 (Tier 4)Source —4.167%Not comparable
Multimodal
BenchmarkDeepSeek V4 Flash (Max)Gemini 2.5 ProResult
Design Arena WebsiteSource 12381197DeepSeek V4 Flash (Max) leads
AA-MMMU-ProSource —74.9%Not comparable
Inst. Following
BenchmarkDeepSeek V4 Flash (Max)Gemini 2.5 ProResult
AA-IFBenchSource 79.2%48.7%DeepSeek V4 Flash (Max) leads
Frequently Asked Questions (4)

Which is better, DeepSeek V4 Flash (Max) or Gemini 2.5 Pro?

DeepSeek V4 Flash (Max) and Gemini 2.5 Pro are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.

Which is better for knowledge tasks, DeepSeek V4 Flash (Max) or Gemini 2.5 Pro?

DeepSeek V4 Flash (Max) has the edge for knowledge tasks in this comparison, averaging 55.3 versus 27.4. Inside this category, HLE is the benchmark that creates the most daylight between them.

Which is better for coding, DeepSeek V4 Flash (Max) or Gemini 2.5 Pro?

DeepSeek V4 Flash (Max) has the edge for coding in this comparison, averaging 68.8 versus 63.8. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.

Which is better for math, DeepSeek V4 Flash (Max) or Gemini 2.5 Pro?

DeepSeek V4 Flash (Max) has the edge for math in this comparison, averaging 94.8 versus 11.6. Gemini 2.5 Pro stays close enough that the answer can still flip depending on your workload.

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