Is Granite 4.2 8B better than Ling 3.1 Flash?

On accuracy they are statistically tied: Granite 4.2 8B scored 36.2% and Ling 3.1 Flash 41.2% on the same 80 questions from open datasets. Similar accuracy; Granite 4.2 8B costs less per question.

Which is cheaper, Granite 4.2 8B or Ling 3.1 Flash?

Granite 4.2 8B is cheaper: $0.000077 per question as billed, against $0.00061. List prices: Granite 4.2 8B $0.06 in / $0.25 out, Ling 3.1 Flash $0.075 in / $0.225 out per million tokens.

Which is faster, Granite 4.2 8B or Ling 3.1 Flash?

Granite 4.2 8B is faster at 60 output tokens per second, against 7. Time to first token: 0.6 s for Granite 4.2 8B, 1.1 s for Ling 3.1 Flash.

Which has the larger context window, Granite 4.2 8B or Ling 3.1 Flash?

Ling 3.1 Flash, with 262k tokens against 131k.

Head to head · tested 27 Oct 2026

Granite 4.2 8B vs Ling 3.1 Flash: accuracy, speed and price

Similar accuracy; Granite 4.2 8B costs less per question.

IBMGranite 4.2 8B36.2% score · #60$0.000077 per question60 tok/s

inclusionAILing 3.1 Flash41.2% score · #54$0.00061 per question7 tok/s

Verdict

Built from the measurements below

Accuracy is too close to call: Granite 4.2 8B scored 36.2% and Ling 3.1 Flash 41.2% on the same 80 questions, a gap within what chance alone could produce.
Granite 4.2 8B is 8.0× cheaper per question as billed ($0.000077 vs $0.00061), reasoning tokens included.
Granite 4.2 8B generates text 8.4× faster: 60 tokens per second against 7.
Granite 4.2 8B starts answering sooner: 0.6 s to the first token, against 1.1 s for Ling 3.1 Flash.
Ling 3.1 Flash accepts more context: 262k tokens against 131k.

Which should you choose?

Choose Granite 4.2 8B for the lower cost per correct answer ($0.00021 against $0.0015), faster streaming, a quicker first token, shorter outputs (about 227 tokens per question against 2,616) and open weights you can run yourself. Choose Ling 3.1 Flash for a 262k-token context window. The widest subject gap is in humanities & social science: Ling 3.1 Flash answered 7 of 9 correctly, Granite 4.2 8B 4 of 9. With so few questions per subject, treat this as a lead to test on your own prompts, not a result.

Accuracy gap -5.0 points (z = -0.65). A winner is called only when z is at least 1.96, the usual 95% threshold. Speed, latency and price need a 10% margin.

Head to head

Same questions, same prompt, same API

Measure	Granite 4.2 8B	Ling 3.1 Flash	Edge
Verification scoreHigher is better	36.2%	41.2%	Too close to call
Cost per questionLower is better	$0.000077	$0.00061	Granite 4.2 8B
Output speedHigher is better	60	7	Granite 4.2 8B
Time to first tokenLower is better	0.6 s	1.1 s	Granite 4.2 8B
End-to-end response timeLower is better	7.3 s	81.3 s	Granite 4.2 8B
Tokens per questionLower is better	227	2,616	Granite 4.2 8B
Context windowHigher is better	131k	262k	Ling 3.1 Flash

Side by side

Bars are scaled to the larger of the two values. The winner on each measure is marked in bold.

Every measure

Granite 4.2 8B first, Ling 3.1 Flash second

Verification scorehigher is better

Granite 4.2 8B36.2%

Ling 3.1 Flash41.2%

Cost per questionlower is better

Granite 4.2 8B$0.000077

Ling 3.1 Flash$0.00061

Output speedhigher is better

Granite 4.2 8B60

Ling 3.1 Flash7

Time to first tokenlower is better

Granite 4.2 8B0.6 s

Ling 3.1 Flash1.1 s

End-to-end response timelower is better

Granite 4.2 8B7.3 s

Ling 3.1 Flash81.3 s

Tokens per questionlower is better

Granite 4.2 8B227

Ling 3.1 Flash2,616

Context windowhigher is better

Granite 4.2 8B131k

Ling 3.1 Flash262k

Score vs. cost per question

Both models in color, every other model in grey

Results by subject and dataset

Questions answered correctly. Small samples: a gap of one or two questions is noise.

Subject	Questions	Granite 4.2 8B	Ling 3.1 Flash
Science	30	13/30	16/30
Engineering	15	4/15	1/15
Medicine	11	1/11	2/11
Economics	9	5/9	6/9
Law	6	2/6	1/6
Humanities & social science	9	4/9	7/9
SuperGPQA dataset	50	11/50	12/50
MMLU-Pro dataset	30	18/30	21/30

Specifications and pricing

From OpenRouter's catalogue, plus the leaderboard's test dates

Specification	Granite 4.2 8B	Ling 3.1 Flash
Creator	IBM	inclusionAI
Released	31 Aug 2026	2 Oct 2026
Weights	Open weights	—
Reasoning	Yes	Yes
Input	text	text
Output	text	text
Context window	131k tokens	262k tokens
Knowledge cutoff	—	—
List price in / out per 1M	$0.06 / $0.25	$0.075 / $0.225
Blended price per 1M (3:1)	$0.11	$0.11
Cheapest host	CoreWeave · $0.06 / $0.15	DeepInfra · $0.075 / $0.225
Hosts on OpenRouter	2	2
Last tested	26 Oct 2026	27 Oct 2026

Compare any two models →

Granite 4.2 8B vs Ling 3.1 Flash: frequently asked questions

Is Granite 4.2 8B better than Ling 3.1 Flash?: On accuracy they are statistically tied: Granite 4.2 8B scored 36.2% and Ling 3.1 Flash 41.2% on the same 80 questions from open datasets. Similar accuracy; Granite 4.2 8B costs less per question.
Which is cheaper, Granite 4.2 8B or Ling 3.1 Flash?: Granite 4.2 8B is cheaper: $0.000077 per question as billed, against $0.00061. List prices: Granite 4.2 8B $0.06 in / $0.25 out, Ling 3.1 Flash $0.075 in / $0.225 out per million tokens.
Which is faster, Granite 4.2 8B or Ling 3.1 Flash?: Granite 4.2 8B is faster at 60 output tokens per second, against 7. Time to first token: 0.6 s for Granite 4.2 8B, 1.1 s for Ling 3.1 Flash.
Which has the larger context window, Granite 4.2 8B or Ling 3.1 Flash?: Ling 3.1 Flash, with 262k tokens against 131k.