Model comparison

DeepSeek V4 Flash vs Qwen3.5-122B-A10B

Data verified July 23, 2026

Head-to-head evidence from 4 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

DeepSeek V4 Flash

DeepSeek

58.88/100

Margin

1.7pts

winning →

Qwen3.5-122B-A10B

Alibaba

60.56/100

0 category wins3 category wins

Public leaderboard positions: DeepSeek V4 Flash #61 (Estimated); Qwen3.5-122B-A10B #47 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V4 Flash and Qwen3.5-122B-A10B share 4 comparable benchmark results. 3 of 8 categories are comparable. 18 results are unique to DeepSeek V4 Flash; 27 to Qwen3.5-122B-A10B.

Updated July 23, 2026

Shared results: 4
DeepSeek V4 Flash only: 18
Qwen3.5-122B-A10B only: 27
Comparable categories: 3 / 8

Pick Qwen3.5-122B-A10B if you want the stronger benchmark profile. DeepSeek V4 Flash only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.

Confidence note. This is a partial-evidence comparison with 4 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

Qwen3.5-122B-A10B has the cleaner BenchAlign overall profile here, landing at 60.56 versus 58.88. It is a real lead, but still close enough that category-level strengths matter more than the headline number.

Qwen3.5-122B-A10B's sharpest advantage is in knowledge, where it averages 83.6 against 38.8. The single biggest benchmark swing on the page is GPQA, 71.2% to 86.6%.

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 Qwen3.5-122B-A10B. That is roughly Infinityx on output cost alone. Qwen3.5-122B-A10B 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 Qwen3.5-122B-A10B.

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 Qwen3.5-122B-A10B
Category	DeepSeek V4 Flash	Δ	Qwen3.5-122B-A10B
Knowledge	DeepSeek V4 Flash38.8	Margin→ 44.8	Qwen3.5-122B-A10B83.6
Coding	DeepSeek V4 Flash64.2	Margin→ 7.8	Qwen3.5-122B-A10B72.0
Agentic	DeepSeek V4 Flash49.1	Margin→ 7.3	Qwen3.5-122B-A10B56.4
Reasoning	DeepSeek V4 FlashNot measured	MarginNo overlap	Qwen3.5-122B-A10B60.2
Math	DeepSeek V4 Flash40.8	MarginNo overlap	Qwen3.5-122B-A10BNot measured
Multilingual	DeepSeek V4 FlashNot measured	MarginNo overlap	Qwen3.5-122B-A10B82.2
Multimodal	DeepSeek V4 FlashNot measured	MarginNo overlap	Qwen3.5-122B-A10B77.2
Inst. Following	DeepSeek V4 FlashNot measured	MarginNo overlap	Qwen3.5-122B-A10B93.4

Decisive benchmark drivers

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

A · DeepSeek V4 FlashB · Qwen3.5-122B-A10B

GPQA
Knowledge
Source ↗
A 71.2%B 86.6%
Winner: Qwen3.5-122B-A10BΔ 15.4
GPQA: DeepSeek V4 Flash scored 71.2%; Qwen3.5-122B-A10B scored 86.6%. Qwen3.5-122B-A10B wins this benchmark.
MMLU-Pro
Knowledge
Source ↗
A 83%B 86.7%
Winner: Qwen3.5-122B-A10BΔ 3.7
MMLU-Pro: DeepSeek V4 Flash scored 83%; Qwen3.5-122B-A10B scored 86.7%. Qwen3.5-122B-A10B wins this benchmark.
SWE-bench Verified
Coding
Source ↗
A 73.7%B 72%
Winner: DeepSeek V4 FlashΔ 1.7
SWE-bench Verified: DeepSeek V4 Flash scored 73.7%; Qwen3.5-122B-A10B scored 72%. DeepSeek V4 Flash wins this benchmark.
Terminal-Bench 2.0
Agentic
Source ↗
A 49.1%B 49.4%
Winner: Qwen3.5-122B-A10BΔ 0.3
Terminal-Bench 2.0: DeepSeek V4 Flash scored 49.1%; Qwen3.5-122B-A10B scored 49.4%. Qwen3.5-122B-A10B wins this benchmark.

Operational comparison

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

Metric	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Comparison
Input / output priceUSD per 1M tokens	DeepSeek V4 Flash$0.14 input / $0.28 output	Qwen3.5-122B-A10B$0 input / $0 output	Qwen3.5-122B-A10B has the lower combined listed price.
Generation speedtokens per second	DeepSeek V4 FlashNot available	Qwen3.5-122B-A10BNot available	A complete speed comparison is not available.
First-answer latencyseconds to first token	DeepSeek V4 FlashNot available	Qwen3.5-122B-A10BNot available	A complete latency comparison is not available.
Context windowmaximum listed tokens	DeepSeek V4 Flash1M	Qwen3.5-122B-A10B262K	DeepSeek V4 Flash lists the larger context window.

Benchmark Deep Dive

AgenticQwen3.5-122B-A10B wins

11 benchmarks

Benchmark	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Result
Terminal-Bench 2.0Source	49.1%	49.4%	Qwen3.5-122B-A10B leads
MCP AtlasSource	64%	—	Not comparable
ToolathlonSource	40.7%	—	Not comparable
Claw-EvalSource	57.8%	—	Not comparable
Gert LabsSource	54.35%	—	Not comparable
BrowseCompSource	—	63.8%	Not comparable
OSWorld-VerifiedSource	—	58%	Not comparable
τ²-bench resultsSource	—	93.6%	Not comparable
AA Agentic IndexSource	—	20.7%	Not comparable
GDPval-AASource	—	23.9%	Not comparable
GDPval-AASource	—	978	Not comparable

CodingQwen3.5-122B-A10B wins

6 benchmarks

Benchmark	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Result
SWE-bench VerifiedSource	73.7%	72%	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
AA Coding IndexSource	—	45.7%	Not comparable
AA-SciCodeSource	—	42.0%	Not comparable

Reasoning

5 benchmarks

Benchmark	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Result
MRCR 1MSource	37.5%	—	Not comparable
CorpusQA 1MSource	15.5%	—	Not comparable
LongBench v2Source	—	60.2%	Not comparable
AA-LCRSource	—	66.7%	Not comparable
CritPtSource	—	0.6%	Not comparable

KnowledgeQwen3.5-122B-A10B wins

13 benchmarks

Benchmark	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Result
MMLU-ProSource	83%	86.7%	Qwen3.5-122B-A10B leads
SimpleQASource	23.1%	—	Not comparable
Chinese-SimpleQASource	71.5%	—	Not comparable
GPQASource	71.2%	86.6%	Qwen3.5-122B-A10B leads
GPQA-DSource	71.2%	—	Not comparable
HLESource	8.1%	—	Not comparable
SuperGPQASource	—	67.1%	Not comparable
Artificial Analysis Intelligence IndexSource	—	32.3%	Not comparable
AA-GPQA DiamondSource	—	85.7%	Not comparable
AA-HLESource	—	23.4%	Not comparable
AA-Omniscience IndexSource	—	-39.6%	Not comparable
AA-Omniscience AccuracySource	—	24.7%	Not comparable
AA-Omniscience Hallucination RateSource	—	85.5%	Not comparable

Math

4 benchmarks

Benchmark	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Result
HMMT Feb 2026Source	40.8%	—	Not comparable
IMOAnswerBenchSource	41.9%	—	Not comparable
ApexSource	1.0%	—	Not comparable
Apex ShortlistSource	9.3%	—	Not comparable

Multilingual

1 benchmarks

Benchmark	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Result
MMLU-ProXSource	—	82.2%	Not comparable

Multimodal

7 benchmarks

Benchmark	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Result
Design Arena WebsiteSource	1238	—	Not comparable
MMMUSource	—	83.9%	Not comparable
MMVUSource	—	74.7%	Not comparable
MathVisionSource	—	86.2%	Not comparable
CharXivSource	—	77.2%	Not comparable
V*Source	—	93.2%	Not comparable
AA-MMMU-ProSource	—	75.0%	Not comparable

Inst. Following

2 benchmarks

Benchmark	DeepSeek V4 Flash	Qwen3.5-122B-A10B	Result
IFEvalSource	—	93.4%	Not comparable
AA-IFBenchSource	—	75.7%	Not comparable

Frequently Asked Questions (4)

Which is better, DeepSeek V4 Flash or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B is ahead on BenchLM's BenchAlign leaderboard, 60.56 to 58.88. The biggest single separator in this matchup is GPQA, where the scores are 71.2% and 86.6%.

Which is better for knowledge tasks, DeepSeek V4 Flash or Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for knowledge tasks in this comparison, averaging 83.6 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 Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for coding in this comparison, averaging 72 versus 64.2. 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 Qwen3.5-122B-A10B?

Qwen3.5-122B-A10B has the edge for agentic tasks in this comparison, averaging 56.4 versus 49.1. Inside this category, Terminal-Bench 2.0 is the benchmark that creates the most daylight between them.

Related Comparisons

Explore More

DeepSeek Compare Pricing Methodology Find Your Best LLM Overall Rankings

Last updated: July 23, 2026

Choose a model with this week’s evidence

Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.

One email each week. Unsubscribe anytime.