Model comparison

DeepSeek-V3.1 vs Granite 4.2 8B

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 40.5 on the Noometry Index. Granite 4.2 8B costs 4.0× less per token, which makes it the better buy when DeepSeek-V3.1's lead doesn't matter for your workload.

Last verified October 10, 2026. 11 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.8

Rank #108 Confirmed

Granite 4.2 8B IBM

40.5

Rank #148 Confirmed

Summary

They share 11 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 5 categories and Granite 4.2 8B in 2 categories; 6 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where DeepSeek-V3.1 leads 60.3 to 49.6.
Granite 4.2 8B is cheaper at $0.06 / $0.25 per million input/output tokens, against $0.25 / $0.95 for DeepSeek-V3.1.
DeepSeek-V3.1 accepts more context: 164K tokens versus 131K.

Side by side

DeepSeek-V3.1 and Granite 4.2 8B specifications
	DeepSeek-V3.1	Granite 4.2 8B
Provider	DeepSeek	IBM
Noometry Index	42.8	40.5
Released	2025-08-21	—
Weights	Open	Open
Context window	164K	131K
Max output	8K	118K
Input $ / M tokens	$0.25	$0.06
Output $ / M tokens	$0.95	$0.25
Results tracked	27	11

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Category by category

Coding Too close to call

DeepSeek-V3.1: 40.3 (#144), Granite 4.2 8B: 40.5 (#137)

Coding benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.2 8B
LMArena Coding	1417	1380
WeirdML	38.4%	—

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.9 (#110), Granite 4.2 8B: 26.6 (#131)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.2 8B
LMArena Hard Prompts	1417	1329
SimpleBench	40%	—
Kagi LLM Benchmark	53.2%	—
DTBench	82.7%	—
LMCA	24.3%	—
Epoch Capabilities Index	139.92	—
ForecastBench	58	—

Math Not comparable

DeepSeek-V3.1: 38.9 (#122), Granite 4.2 8B: —

Math benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.2 8B
LMArena Math	1420	—

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.7 (#90), Granite 4.2 8B: 38.4 (#145)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.2 8B
LMArena Expert	1405	1384
Vectara Hallucination Rate	5.5%	—

Multilingual DeepSeek-V3.1 leads

DeepSeek-V3.1: 51.6 (#106), Granite 4.2 8B: 44.5 (#178)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.2 8B
LMArena Non-English	1400	1302
LMArena Chinese	1469	1366
LMArena Russian	1405	1285
LMArena French	1447	—
LMArena German	1411	—
LMArena Japanese	1378	—
LMArena Korean	1337	—
LMArena Spanish	1431	—

Instruction Following DeepSeek-V3.1 leads

DeepSeek-V3.1: 73.9 (#110), Granite 4.2 8B: 68.7 (#184)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.2 8B
LMArena Instruction Following	1400	1301

Long Context Granite 4.2 8B leads

DeepSeek-V3.1: 36.3 (#232), Granite 4.2 8B: 40.3 (#159)

Long Context benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.2 8B
LMArena Longer Query	1422	1324
Fiction.LiveBench	52.8%	—

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.3 (#98), Granite 4.2 8B: 49.6 (#189)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.2 8B
LMArena Text	1420	1320
LMArena Creative Writing	1401	1236
LMArena Multi-Turn	1408	1301
EQ-Bench Creative Writing	1436	—

Frequently asked questions

Is DeepSeek-V3.1 better than Granite 4.2 8B?

Which is cheaper, DeepSeek-V3.1 or Granite 4.2 8B?

Granite 4.2 8B is cheaper. It lists at $0.06 per million input tokens and $0.25 per million output tokens; DeepSeek-V3.1 lists at $0.25 and $0.95.

Is DeepSeek-V3.1 or Granite 4.2 8B better for coding?

They score almost the same on coding (40.3 vs 40.5); test both on your own repository before choosing.

Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 131K.

How many benchmarks do DeepSeek-V3.1 and Granite 4.2 8B share?

11 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Granite 4.2 8B has 11.