DeepSeek-V3.2 vs Granite 4.2 3B
Wins 4 of 6 areas
Coding · Agents · Reasoning · Long documents
Wins 1 of 6 areas
Following instructions
DeepSeek-V3.2 is the stronger all-rounder.Granite 4.2 3B is cheaper and better at following instructions.
Scores updated · 20 tests both models report · How we compare
Where each one wins
Tests won in each of the six areas where both have results. Each piece is one test, so a longer bar means more evidence; grey means the two scored within a point of each other.
- CodingWriting and fixing software30DeepSeek-V3.23 of 3 tests
- ReasoningHard problems that need careful thinking30DeepSeek-V3.23 of 3 tests
- AgentsCarrying out multi-step tasks on its own20DeepSeek-V3.22 of 2 tests
- Long documentsFinding answers in very long texts10DeepSeek-V3.21 of 1 test
- Following instructionsDoing exactly what it is asked01Granite 4.2 3B1 of 1 test
- FactsGetting facts right instead of making them up11Even1 each
Long documents and following instructions rest on a single test each.
What it costs
Prices per million tokens, roughly 750,000 words. The bars show the cost of a million tokens read plus a million written.
Granite 4.2 3B costs 79% less for the same work.
The biggest differences
The tests each model wins by the widest margin, up to three each. Scores are out of 100.
Where DeepSeek-V3.2 pulls ahead
- Reasons across sets of long documentsAA-LCR+49points ahead
- Command-line tasks in a real terminalTerminal-Bench 2.1+32.9points ahead
- Graduate-level biology, physics and chemistry questionsGPQA Diamond+28.1points ahead
Where Granite 4.2 3B pulls ahead
- Avoids making up answers it doesn't knowAA-Omniscience · Non-hallucination+56.4points ahead
- Follows unfamiliar, precisely checkable instructionsIFBench+13.6points ahead
Every test, side by side
All 20 tests both models report. The winning score is in its model's colour; marks a score checked independently.
CodingDeepSeek-V3.2
- Terminal-Bench 2.1DeepSeek-V3.2 by 32.946.813.9+32.9
- LiveCodeBench v6DeepSeek-V3.2 by 13.683.369.7+13.6
- SciCodeDeepSeek-V3.2 by 13.638.925.3+13.6
AgentsDeepSeek-V3.2
- τ-Bench V3 · BankingDeepSeek-V3.2 by 13.218.85.6+13.2
- GDPValDeepSeek-V3.2 by 9.69.60+9.6
ReasoningDeepSeek-V3.2
- GPQA DiamondDeepSeek-V3.2 by 28.18455.9+28.1
- Humanity's Last ExamDeepSeek-V3.2 by 1824.66.6+18
- CritPtDeepSeek-V3.2 by 2.92.90+2.9
FactsEven
- AA-Omniscience · Non-hallucinationGranite 4.2 3B by 56.417.373.7+56.4
- AA-Omniscience · AccuracyDeepSeek-V3.2 by 23.8339.2+23.8
Following instructionsGranite 4.2 3B
- IFBenchGranite 4.2 3B by 13.660.774.3+13.6
Other results8 tests, not counted
Tests outside the eight areas. They are not counted above: several are summary scores built from other tests, or the same test under another name.
- Artificial Analysis Coding IndexDeepSeek-V3.2 by 26.744.217.5+26.7
- HMMT 2025DeepSeek-V3.2 by 23.590.266.7+23.5
- τ³-BenchDeepSeek-V3.2 by 23.469.245.8+23.4
- MMLU-ProDeepSeek-V3.2 by 17.28567.8+17.2
- AIME 2025DeepSeek-V3.2 by 14.893.178.3+14.8
- AA IntelligenceDeepSeek-V3.2 by 12.421.59.1+12.4
- AIME25 no toolsDeepSeek-V3.2 by 1189.378.3+11
- AA-OmniscienceGranite 4.2 3B by 7.8-22.5-14.7+7.8
Questions people ask
Which is better, DeepSeek-V3.2 or Granite 4.2 3B?
DeepSeek-V3.2 wins four of the six areas where both have results: coding, agents, reasoning and long documents. Granite 4.2 3B wins following instructions, and costs 79% less. They are level on facts.
Which is better for coding?
DeepSeek-V3.2. It wins 3 of the 3 coding tests both models report; Granite 4.2 3B wins none.
Which is cheaper?
DeepSeek-V3.2 costs $0.28 per million input tokens and $0.42 per million output tokens; Granite 4.2 3B costs $0.03 and $0.12. That makes Granite 4.2 3B about 79% cheaper for the same work.
How do you compare the two?
We use the 20 benchmark tests both models have published scores on. The verdict counts the 12 tests in the eight capability areas, and a gap under one point (ten on rating-style scales) counts as a tie. The other 8 are listed but not counted, because several are summary scores or repeat a test. Each score is the one shown on the model's own page.