Model comparison

DeepSeek-V3.1-Terminus vs Granite 4.2 8B

DeepSeek-V3.1-Terminus is the stronger model overall, scoring 42.6 to 40.0 on the Noometry Index. Granite 4.2 8B costs 4.4× less per token, which makes it the better buy when DeepSeek-V3.1-Terminus's lead doesn't matter for your workload.

Last verified October 10, 2026. 9 shared benchmarks.

DeepSeek-V3.1-Terminus

DeepSeek

42.6

Rank #96 Confirmed

Granite 4.2 8B IBM

40.0

Rank #143 Confirmed

Summary

They share 9 benchmarks with published results for both. DeepSeek-V3.1-Terminus scores higher in 6 categories and Granite 4.2 8B in 0 categories; 5 gaps are clear of the uncertainty.
The widest gap is in writing & preference, where DeepSeek-V3.1-Terminus leads 61.3 to 49.8.
Granite 4.2 8B is cheaper at $0.06 / $0.25 per million input/output tokens, against $0.30 / $1 for DeepSeek-V3.1-Terminus.
DeepSeek-V3.1-Terminus accepts more context: 164K tokens versus 131K.

Side by side

DeepSeek-V3.1-Terminus and Granite 4.2 8B specifications
	DeepSeek-V3.1-Terminus	Granite 4.2 8B
Provider	DeepSeek	IBM
Noometry Index	42.6	40.0
Released	2025-09-22	—
Weights	Open	Open
Context window	164K	131K
Max output	66K	118K
Input $ / M tokens	$0.30	$0.06
Output $ / M tokens	$1	$0.25
Results tracked	16	11

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Category by category

Coding DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 41.5 (#114), Granite 4.2 8B: 39.9 (#138)

Coding benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Granite 4.2 8B
LMArena Coding	1426	1379
SciCode	40.6%	—
ALE-Bench	745.17	—

Reasoning Too close to call

DeepSeek-V3.1-Terminus: 25.7 (#126), Granite 4.2 8B: 25.5 (#130)

Reasoning benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Granite 4.2 8B
LMArena Hard Prompts	1427	1327
Kagi LLM Benchmark	57.4%	—
CritPt	1.7%	—
DTBench	81.3%	—
LMCA	28.6%	—

Math Not comparable

DeepSeek-V3.1-Terminus: 35.7 (#138), Granite 4.2 8B: —

Math benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Granite 4.2 8B
LMArena Math	1402	—

Knowledge Not comparable

DeepSeek-V3.1-Terminus: —, Granite 4.2 8B: 37.7 (#144)

Knowledge benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Granite 4.2 8B
LMArena Expert	—	1380

Multilingual DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 52.3 (#87), Granite 4.2 8B: 44.5 (#173)

Multilingual benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Granite 4.2 8B
LMArena Non-English	1407	1299
LMArena Russian	1434	1283
LMArena Chinese	—	1361

Instruction Following DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 74.4 (#96), Granite 4.2 8B: 68.7 (#183)

Instruction Following benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Granite 4.2 8B
LMArena Instruction Following	1406	1298

Long Context DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 43.5 (#88), Granite 4.2 8B: 40.2 (#154)

Long Context benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Granite 4.2 8B
LMArena Longer Query	1426	1323

Writing & Preference DeepSeek-V3.1-Terminus leads

DeepSeek-V3.1-Terminus: 61.3 (#87), Granite 4.2 8B: 49.8 (#183)

Writing & Preference benchmarks
Benchmark	DeepSeek-V3.1-Terminus	Granite 4.2 8B
LMArena Text	1420	1319
LMArena Creative Writing	1404	1238
LMArena Multi-Turn	1411	1299

Frequently asked questions

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

Which is cheaper, DeepSeek-V3.1-Terminus 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-Terminus lists at $0.30 and $1.

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

DeepSeek-V3.1-Terminus scores higher on coding benchmarks: 41.5 versus 39.9 in the Noometry coding category.

Which has the bigger context window?

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

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

9 benchmarks have published results for both models. DeepSeek-V3.1-Terminus has 16 scored results on Noometry and Granite 4.2 8B has 11.