Model comparison

DeepSeek-V3.1 vs Granite 4.0 Micro

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 29.0 on the Noometry Index. Granite 4.0 Micro costs 10× less per token, which makes it the better buy when DeepSeek-V3.1's lead doesn't matter for your workload.

Last verified October 11, 2026. 0 shared benchmarks.

DeepSeek-V3.1

DeepSeek

42.8

Rank #108 Confirmed

Granite 4.0 Micro IBM

29.0

Rank #318 Confirmed

Summary

The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.7 to 9.9.
Granite 4.0 Micro is cheaper at $0.017 / $0.11 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 4.0 Micro specifications
	DeepSeek-V3.1	Granite 4.0 Micro
Provider	DeepSeek	IBM
Noometry Index	42.8	29.0
Released	2025-08-21	2025-10-02
Weights	Open	Open
Context window	164K	131K
Max output	8K	118K
Input $ / M tokens	$0.25	$0.017
Output $ / M tokens	$0.95	$0.11
Results tracked	27	8

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Category by category

Coding Not comparable

DeepSeek-V3.1: 40.3 (#144), Granite 4.0 Micro: —

Coding benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.0 Micro
WeirdML	38.4%	—
LMArena Coding	1417	—

Reasoning DeepSeek-V3.1 leads

DeepSeek-V3.1: 27.9 (#110), Granite 4.0 Micro: 19.2 (#265)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.0 Micro
SimpleBench	40%	—
Kagi LLM Benchmark	53.2%	—
Chess Puzzles	—	0%
LMArena Hard Prompts	1417	—
DTBench	82.7%	—
LMCA	24.3%	—
Epoch Capabilities Index	139.92	—
ForecastBench	58	—

Math DeepSeek-V3.1 leads

DeepSeek-V3.1: 38.9 (#122), Granite 4.0 Micro: 12.0 (#307)

Math benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.0 Micro
OTIS Mock AIME 2024-2025	—	2.8%
Omni-MATH	—	20.9%
LMArena Math	1420	—

Knowledge DeepSeek-V3.1 leads

DeepSeek-V3.1: 43.7 (#90), Granite 4.0 Micro: 9.9 (#304)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.0 Micro
GPQA Diamond	—	28.3%
MMLU-Pro	—	39.5%
Vectara Hallucination Rate	5.5%	—
GPQA (HELM)	—	30.7%
LMArena Expert	1405	—

Multilingual Not comparable

DeepSeek-V3.1: 51.6 (#106), Granite 4.0 Micro: —

Multilingual benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.0 Micro
LMArena Non-English	1400	—
LMArena Chinese	1469	—
LMArena French	1447	—
LMArena German	1411	—
LMArena Japanese	1378	—
LMArena Korean	1337	—
LMArena Russian	1405	—
LMArena Spanish	1431	—

Instruction Following DeepSeek-V3.1 leads

DeepSeek-V3.1: 73.9 (#110), Granite 4.0 Micro: 69.9 (#169)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.0 Micro
IFEval	—	84.9%
LMArena Instruction Following	1400	—

Long Context Not comparable

DeepSeek-V3.1: 36.3 (#232), Granite 4.0 Micro: —

Long Context benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.0 Micro
Fiction.LiveBench	52.8%	—
LMArena Longer Query	1422	—

Writing & Preference DeepSeek-V3.1 leads

DeepSeek-V3.1: 60.3 (#98), Granite 4.0 Micro: 46.7 (#216)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1	Granite 4.0 Micro
LMArena Text	1420	—
LMArena Creative Writing	1401	—
EQ-Bench Creative Writing	1436	—
WildBench	—	67%
LMArena Multi-Turn	1408	—

Frequently asked questions

Is DeepSeek-V3.1 better than Granite 4.0 Micro?

Which is cheaper, DeepSeek-V3.1 or Granite 4.0 Micro?

Granite 4.0 Micro is cheaper. It lists at $0.017 per million input tokens and $0.11 per million output tokens; DeepSeek-V3.1 lists at $0.25 and $0.95.

Which has the bigger context window?

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

How many benchmarks do DeepSeek-V3.1 and Granite 4.0 Micro share?

0 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Granite 4.0 Micro has 8.