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Model comparison

DeepSeek V4 Flash vs Qwen3.5-35B-A3B

Data verified

Head-to-head evidence from 5 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

58.88/100
Margin
1.9pts
← winning
56.97/100
1 category wins2 category wins

Public leaderboard positions: DeepSeek V4 Flash #61 (Estimated); Qwen3.5-35B-A3B #72 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V4 Flash and Qwen3.5-35B-A3B share 5 comparable benchmark results. 3 of 8 categories are comparable. 17 results are unique to DeepSeek V4 Flash; 23 to Qwen3.5-35B-A3B.

Updated July 23, 2026
Shared results
5
DeepSeek V4 Flash only
17
Qwen3.5-35B-A3B only
23
Comparable categories
3 / 8

Pick DeepSeek V4 Flash if you want the stronger benchmark profile. Qwen3.5-35B-A3B only becomes the better choice if knowledge is the priority or you want the cheaper token bill.

Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 3 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 has the cleaner BenchAlign overall profile here, landing at 58.88 versus 56.97. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

DeepSeek V4 Flash's sharpest advantage is in coding, where it averages 64.2 against 60.6. The single biggest benchmark swing on the page is GPQA, 71.2% to 84.2%. Qwen3.5-35B-A3B does hit back in knowledge, so the answer changes if that is the part of the workload you care about most.

DeepSeek V4 Flash is also the more expensive model on tokens at $0.14 input / $0.28 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Qwen3.5-35B-A3B. That is roughly Infinityx on output cost alone. Qwen3.5-35B-A3B is the reasoning model in the pair, while DeepSeek V4 Flash 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. DeepSeek V4 Flash gives you the larger context window at 1M, compared with 262K for Qwen3.5-35B-A3B.

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 and Qwen3.5-35B-A3B
CategoryDeepSeek V4 FlashΔQwen3.5-35B-A3B
KnowledgeDeepSeek V4 Flash38.8Margin 42.8Qwen3.5-35B-A3B81.6
CodingDeepSeek V4 Flash64.2Margin 3.6Qwen3.5-35B-A3B60.6
AgenticDeepSeek V4 Flash49.1Margin 1.9Qwen3.5-35B-A3B51.0
ReasoningDeepSeek V4 FlashNot measuredMarginNo overlapQwen3.5-35B-A3B59.0
MathDeepSeek V4 Flash40.8MarginNo overlapQwen3.5-35B-A3BNot measured
MultilingualDeepSeek V4 FlashNot measuredMarginNo overlapQwen3.5-35B-A3B81.0
Inst. FollowingDeepSeek V4 FlashNot measuredMarginNo overlapQwen3.5-35B-A3B91.9

Decisive benchmark drivers

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

More
A · DeepSeek V4 FlashB · Qwen3.5-35B-A3B
  1. GPQA

    Knowledge
    Source ↗
    A 71.2%B 84.2%
    Winner: Qwen3.5-35B-A3BΔ 13
    GPQA: DeepSeek V4 Flash scored 71.2%; Qwen3.5-35B-A3B scored 84.2%. Qwen3.5-35B-A3B wins this benchmark.
  2. Terminal-Bench 2.0

    Agentic
    Source ↗
    A 49.1%B 40.5%
    Winner: DeepSeek V4 FlashΔ 8.6
    Terminal-Bench 2.0: DeepSeek V4 Flash scored 49.1%; Qwen3.5-35B-A3B scored 40.5%. DeepSeek V4 Flash wins this benchmark.
  3. SWE-bench Verified

    Coding
    Source ↗
    A 73.7%B 69.2%
    Winner: DeepSeek V4 FlashΔ 4.5
    SWE-bench Verified: DeepSeek V4 Flash scored 73.7%; Qwen3.5-35B-A3B scored 69.2%. DeepSeek V4 Flash wins this benchmark.
  4. MMLU-Pro

    Knowledge
    Source ↗
    A 83%B 85.3%
    Winner: Qwen3.5-35B-A3BΔ 2.3
    MMLU-Pro: DeepSeek V4 Flash scored 83%; Qwen3.5-35B-A3B scored 85.3%. Qwen3.5-35B-A3B wins this benchmark.

Operational comparison

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

MetricDeepSeek V4 FlashQwen3.5-35B-A3BComparison
Input / output priceUSD per 1M tokensDeepSeek V4 Flash$0.14 input / $0.28 outputQwen3.5-35B-A3B$0 input / $0 outputQwen3.5-35B-A3B has the lower combined listed price.
Generation speedtokens per secondDeepSeek V4 FlashNot availableQwen3.5-35B-A3BNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V4 FlashNot availableQwen3.5-35B-A3BNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V4 Flash1MQwen3.5-35B-A3B262KDeepSeek V4 Flash lists the larger context window.

Benchmark Deep Dive

AgenticQwen3.5-35B-A3B wins
BenchmarkDeepSeek V4 FlashQwen3.5-35B-A3BResult
Terminal-Bench 2.0Source 49.1%40.5%DeepSeek V4 Flash leads
MCP AtlasSource 64%Not comparable
ToolathlonSource 40.7%Not comparable
Claw-EvalSource 57.8%Not comparable
Gert LabsSource 54.35%28.96%DeepSeek V4 Flash leads
BrowseCompSource 61%Not comparable
OSWorld-VerifiedSource 54.5%Not comparable
τ²-bench resultsSource 89.2%Not comparable
CodingDeepSeek V4 Flash wins
BenchmarkDeepSeek V4 FlashQwen3.5-35B-A3BResult
SWE-bench VerifiedSource 73.7%69.2%DeepSeek V4 Flash leads
SWE-bench ProSource 49.1%Not comparable
SWE MultilingualSource 69.7%Not comparable
Terminal-Bench 2.0Source 49.1%Not comparable
SWE-RebenchSource 53.7%Not comparable
AA-SciCodeSource 37.7%Not comparable
Reasoning
BenchmarkDeepSeek V4 FlashQwen3.5-35B-A3BResult
MRCR 1MSource 37.5%Not comparable
CorpusQA 1MSource 15.5%Not comparable
LongBench v2Source 59%Not comparable
AA-LCRSource 62.7%Not comparable
CritPtSource 0.9%Not comparable
KnowledgeQwen3.5-35B-A3B wins
BenchmarkDeepSeek V4 FlashQwen3.5-35B-A3BResult
MMLU-ProSource 83%85.3%Qwen3.5-35B-A3B leads
SimpleQASource 23.1%Not comparable
Chinese-SimpleQASource 71.5%Not comparable
GPQASource 71.2%84.2%Qwen3.5-35B-A3B leads
GPQA-DSource 71.2%Not comparable
HLESource 8.1%Not comparable
SuperGPQASource 63.4%Not comparable
Artificial Analysis Intelligence IndexSource 29.3%Not comparable
AA-GPQA DiamondSource 84.5%Not comparable
AA-HLESource 19.7%Not comparable
AA-Omniscience IndexSource -46.4%Not comparable
AA-Omniscience AccuracySource 20.5%Not comparable
AA-Omniscience Hallucination RateSource 84.0%Not comparable
Math
BenchmarkDeepSeek V4 FlashQwen3.5-35B-A3BResult
HMMT Feb 2026Source 40.8%Not comparable
IMOAnswerBenchSource 41.9%Not comparable
ApexSource 1.0%Not comparable
Apex ShortlistSource 9.3%Not comparable
Multilingual
BenchmarkDeepSeek V4 FlashQwen3.5-35B-A3BResult
MMLU-ProXSource 81%Not comparable
Multimodal
BenchmarkDeepSeek V4 FlashQwen3.5-35B-A3BResult
Design Arena WebsiteSource 1238Not comparable
MMMUSource 81.4%Not comparable
MMVUSource 72.3%Not comparable
MathVisionSource 83.9%Not comparable
V*Source 92.7%Not comparable
AA-MMMU-ProSource 72.7%Not comparable
Inst. Following
BenchmarkDeepSeek V4 FlashQwen3.5-35B-A3BResult
IFEvalSource 91.9%Not comparable
AA-IFBenchSource 72.5%Not comparable
Frequently Asked Questions (4)

Which is better, DeepSeek V4 Flash or Qwen3.5-35B-A3B?

DeepSeek V4 Flash is ahead on BenchLM's BenchAlign leaderboard, 58.88 to 56.97. The biggest single separator in this matchup is GPQA, where the scores are 71.2% and 84.2%.

Which is better for knowledge tasks, DeepSeek V4 Flash or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B has the edge for knowledge tasks in this comparison, averaging 81.6 versus 38.8. Inside this category, GPQA is the benchmark that creates the most daylight between them.

Which is better for coding, DeepSeek V4 Flash or Qwen3.5-35B-A3B?

DeepSeek V4 Flash has the edge for coding in this comparison, averaging 64.2 versus 60.6. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.

Which is better for agentic tasks, DeepSeek V4 Flash or Qwen3.5-35B-A3B?

Qwen3.5-35B-A3B has the edge for agentic tasks in this comparison, averaging 51 versus 49.1. Inside this category, Gert Labs is the benchmark that creates the most daylight between them.

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Last updated: July 23, 2026

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