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Model comparison

DeepSeek V3 vs Step 3.7 Flash

Data verified

Head-to-head evidence from 17 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

DeepSeek
44.84/100
Margin
5.9pts
winning →
50.76/100
0 category wins1 category wins

BenchAlign evidence: DeepSeek V3 supported; Step 3.7 Flash estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3 and Step 3.7 Flash share 17 comparable benchmark results. 1 of 8 categories are comparable. 6 results are unique to DeepSeek V3; 13 to Step 3.7 Flash.

Updated July 16, 2026
Shared results
17
DeepSeek V3 only
6
Step 3.7 Flash only
13
Comparable categories
1 / 8

Pick Step 3.7 Flash if you want the stronger benchmark profile. DeepSeek V3 only becomes the better choice if you want the cheaper token bill or you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 17 shared benchmark results across 6 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Step 3.7 Flash is clearly ahead on the provisional aggregate, 57 to 38. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Step 3.7 Flash's sharpest advantage is in coding, where it averages 56.3 against 38.9.

Step 3.7 Flash is also the more expensive model on tokens at $0.20 input / $1.15 output per 1M tokens, versus $0.27 input / $1.10 output per 1M tokens for DeepSeek V3. Step 3.7 Flash is the reasoning model in the pair, while DeepSeek V3 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. Step 3.7 Flash gives you the larger context window at 256K, compared with 128K for DeepSeek V3.

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 V3 and Step 3.7 Flash
CategoryDeepSeek V3ΔStep 3.7 Flash
CodingDeepSeek V338.9Margin 17.4Step 3.7 Flash56.3
AgenticDeepSeek V3Not measuredMarginNo overlapStep 3.7 Flash66.4
KnowledgeDeepSeek V372.8MarginNo overlapStep 3.7 FlashNot measured
MathDeepSeek V31.7MarginNo overlapStep 3.7 FlashNot measured
Inst. FollowingDeepSeek V386.1MarginNo overlapStep 3.7 FlashNot measured

Operational comparison

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

MetricDeepSeek V3Step 3.7 FlashComparison
Input / output priceUSD per 1M tokensDeepSeek V3$0.27 input / $1.1 outputStep 3.7 Flash$0.2 input / $1.15 outputStep 3.7 Flash has the lower combined listed price.
Generation speedtokens per secondDeepSeek V3Not availableStep 3.7 FlashNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V3Not availableStep 3.7 FlashNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V3128KStep 3.7 Flash256KStep 3.7 Flash lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3Step 3.7 FlashResult
AA Agentic IndexSource 1.6%21.5%Step 3.7 Flash leads
τ²-bench resultsSource 22.8%98.5%Step 3.7 Flash leads
GDPval-AASource 0.0%25.9%Step 3.7 Flash leads
GDPval-AASource 2171017Step 3.7 Flash leads
Terminal-Bench 2.0Source 59.5%Not comparable
BrowseCompSource 75.8%Not comparable
DeepSearchQASource 92.8%Not comparable
ToolathlonSource 49.5%Not comparable
Claw-EvalSource 67.1%Not comparable
HLE w/ toolsSource 47.2%Not comparable
Gert LabsSource 51.57%Not comparable
APEX-Agents-AASource 14.8%Not comparable
CodingStep 3.7 Flash wins
BenchmarkDeepSeek V3Step 3.7 FlashResult
LiveCodeBenchSource 37.6%Not comparable
SWE-bench VerifiedSource 42%Not comparable
AA Coding IndexSource 23.0%39.6%Step 3.7 Flash leads
Terminal-Bench HardSource 6.8%35.6%Step 3.7 Flash leads
AA-SciCodeSource 35.4%40.0%Step 3.7 Flash leads
SWE-bench ProSource 56.3%Not comparable
Terminal-Bench 2.0Source 59.5%Not comparable
Reasoning
BenchmarkDeepSeek V3Step 3.7 FlashResult
AA-LCRSource 29.0%63.7%Step 3.7 Flash leads
CritPtSource 0.0%2.3%Step 3.7 Flash leads
Knowledge
BenchmarkDeepSeek V3Step 3.7 FlashResult
GPQASource 59.1%Not comparable
MMLU-ProSource 75.9%Not comparable
Artificial Analysis Intelligence IndexSource 14.2%30.3%Step 3.7 Flash leads
AA-GPQA DiamondSource 55.7%80.9%Step 3.7 Flash leads
AA-HLESource 3.6%19.9%Step 3.7 Flash leads
AA-Omniscience IndexSource -41.3%-37.5%Step 3.7 Flash leads
AA-Omniscience AccuracySource 25.4%25.4%Tie
AA-Omniscience Hallucination RateSource 89.4%84.4%Step 3.7 Flash leads
Math
BenchmarkDeepSeek V3Step 3.7 FlashResult
FrontierMath v2 (Tiers 1-3)Source 1.724%Not comparable
Multimodal
BenchmarkDeepSeek V3Step 3.7 FlashResult
Design Arena WebsiteSource 11541218Step 3.7 Flash leads
SimpleVQASource 79.2%Not comparable
V*Source 95.3%Not comparable
AA-MMMU-ProSource 75.3%Not comparable
Inst. Following
BenchmarkDeepSeek V3Step 3.7 FlashResult
IFEvalSource 86.1%Not comparable
AA-IFBenchSource 34.8%67.3%Step 3.7 Flash leads
Frequently Asked Questions (2)

Which is better, DeepSeek V3 or Step 3.7 Flash?

Step 3.7 Flash is ahead on BenchLM's provisional leaderboard, 57 to 38.

Which is better for coding, DeepSeek V3 or Step 3.7 Flash?

Step 3.7 Flash has the edge for coding in this comparison, averaging 56.3 versus 38.9. Inside this category, Terminal-Bench Hard is the benchmark that creates the most daylight between them.

Self-host vs API cost

Estimates at 50,000 req/day · 1000 tokens/req average.

DeepSeek V3
API / mo$1,028
Self-host / mo$18,221
Break-even1.2B/day
Step 3.7 Flash
API / mo$1,012
Self-host / moNot listed
Break-even
Proprietary model — self-hosting not applicable.
Model the full break-even

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Last updated: July 16, 2026

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