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Model comparison

DeepSeek V3.2 vs Inkling

Data verified

Head-to-head evidence from 9 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.

55.3/100
Margin
16.7pts
winning →
Thinking Machines Lab
72/100
0 category wins2 category wins

Verified leaderboard positions: DeepSeek V3.2 unranked; Inkling #17

BenchAlign evidence: DeepSeek V3.2 supported; Inkling not scored. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.

Evidence parity. DeepSeek V3.2 and Inkling share 9 comparable benchmark results. 2 of 8 categories are comparable. 11 results are unique to DeepSeek V3.2; 23 to Inkling.

Updated July 16, 2026
Shared results
9
DeepSeek V3.2 only
11
Inkling only
23
Comparable categories
2 / 8

Pick Inkling if you want the stronger benchmark profile. DeepSeek V3.2 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 9 shared benchmark results across 3 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.

Why this result

Inkling is clearly ahead on the provisional aggregate, 72 to 54. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.

Inkling's sharpest advantage is in mathematics, where it averages 97.1 against 17.1.

Inkling is also the more expensive model on tokens at $1.87 input / $4.68 output per 1M tokens, versus $0.28 input / $0.42 output per 1M tokens for DeepSeek V3.2. That is roughly 11.1x on output cost alone. Inkling is the reasoning model in the pair, while DeepSeek V3.2 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. Inkling gives you the larger context window at 1M, compared with 128K for DeepSeek V3.2.

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 V3.2 and Inkling
CategoryDeepSeek V3.2ΔInkling
MathDeepSeek V3.217.1Margin 80.0Inkling97.1
CodingDeepSeek V3.260.9Margin 7.7Inkling68.6
AgenticDeepSeek V3.2Not measuredMarginNo overlapInkling69.4
KnowledgeDeepSeek V3.2Not measuredMarginNo overlapInkling51.7
MultimodalDeepSeek V3.2Not measuredMarginNo overlapInkling76.5
Inst. FollowingDeepSeek V3.2Not measuredMarginNo overlapInkling79.8

Operational comparison

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

MetricDeepSeek V3.2InklingComparison
Input / output priceUSD per 1M tokensDeepSeek V3.2$0.28 input / $0.42 outputInkling$1.87 input / $4.68 outputDeepSeek V3.2 has the lower combined listed price.
Generation speedtokens per secondDeepSeek V3.235 tok/sInklingNot availableA complete speed comparison is not available.
First-answer latencyseconds to first tokenDeepSeek V3.23.75 sInklingNot availableA complete latency comparison is not available.
Context windowmaximum listed tokensDeepSeek V3.2128KInkling1MInkling lists the larger context window.

Benchmark Deep Dive

Agentic
BenchmarkDeepSeek V3.2InklingResult
Claw-EvalSource 40.2%Not comparable
VITA-BenchSource 18.5%Not comparable
τ²-bench resultsSource 78.9%Not comparable
Gert LabsSource 29.57%Not comparable
Terminal-Bench 2.0Source 63.8%Not comparable
BrowseCompSource 77.1%Not comparable
MCP AtlasSource 74.1%Not comparable
Design Arena Agentic Web DevSource 1258Not comparable
AA Agentic IndexSource 32.3%Not comparable
GDPval-AASource 36.9%Not comparable
GDPval-AASource 1239Not comparable
AA BriefcaseSource 836Not comparable
AA Tau3 BankingSource 23.7%Not comparable
CodingInkling wins
BenchmarkDeepSeek V3.2InklingResult
SWE-RebenchSource 60.9%Not comparable
React Native EvalsSource 71.5%Not comparable
Terminal-Bench HardSource 32.6%Not comparable
AA-SciCodeSource 38.7%46.1%Inkling leads
SWE-bench VerifiedSource 77.6%Not comparable
SWE-bench ProSource 54.3%Not comparable
Terminal-Bench 2.0Source 63.8%Not comparable
AA Coding IndexSource 52.1%Not comparable
Reasoning
BenchmarkDeepSeek V3.2InklingResult
AA-LCRSource 39.0%63.3%Inkling leads
CritPtSource 0.9%5.4%Inkling leads
Knowledge
BenchmarkDeepSeek V3.2InklingResult
Artificial Analysis Intelligence IndexSource 24.7%40.7%Inkling leads
AA-GPQA DiamondSource 75.1%87.2%Inkling leads
AA-HLESource 10.5%29.7%Inkling leads
AA-Omniscience IndexSource -46.7%2.1%Inkling leads
AA-Omniscience AccuracySource 24.2%40.0%Inkling leads
AA-Omniscience Hallucination RateSource 93.5%63.1%Inkling leads
GPQASource 87.9%Not comparable
GPQA-DSource 87.9%Not comparable
HLESource 46%Not comparable
HLE w/o toolsSource 30%Not comparable
MathInkling wins
BenchmarkDeepSeek V3.2InklingResult
FrontierMath v2 (Tiers 1-3)Source 22.100%Not comparable
FrontierMath v2 (Tier 4)Source 2.100%Not comparable
AIME26Source 97.1%Not comparable
Multimodal
BenchmarkDeepSeek V3.2InklingResult
Design Arena WebsiteSource 1208Not comparable
MMMU-ProSource 73.5%Not comparable
CharXivSource 82%Not comparable
CharXiv w/o toolsSource 78.1%Not comparable
AA-MMMU-ProSource 73.5%Not comparable
Inst. Following
BenchmarkDeepSeek V3.2InklingResult
AA-IFBenchSource 49.0%Not comparable
IFBenchSource 79.8%Not comparable
Frequently Asked Questions (3)

Which is better, DeepSeek V3.2 or Inkling?

Inkling is ahead on BenchLM's provisional leaderboard, 72 to 54.

Which is better for coding, DeepSeek V3.2 or Inkling?

Inkling has the edge for coding in this comparison, averaging 68.6 versus 60.9. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.

Which is better for math, DeepSeek V3.2 or Inkling?

Inkling has the edge for math in this comparison, averaging 97.1 versus 17.1. DeepSeek V3.2 stays close enough that the answer can still flip depending on your workload.

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Last updated: July 16, 2026

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