Is Llama 3.3 70B Instruct better than Solar Pro 4?

On accuracy they are statistically tied: Llama 3.3 70B Instruct scored 42.5% and Solar Pro 4 45.0% on the same 80 questions from open datasets. Similar accuracy; Llama 3.3 70B Instruct costs less per question.

Which is cheaper, Llama 3.3 70B Instruct or Solar Pro 4?

Llama 3.3 70B Instruct is cheaper: $0.00053 per question as billed, against $0.0018. List prices: Llama 3.3 70B Instruct $0.1 in / $0.32 out, Solar Pro 4 $0.15 in / $0.6 out per million tokens.

Which is faster, Llama 3.3 70B Instruct or Solar Pro 4?

Solar Pro 4 is faster at 91 output tokens per second, against 42. Time to first token: 0.7 s for Llama 3.3 70B Instruct, 0.6 s for Solar Pro 4.

Which has the larger context window, Llama 3.3 70B Instruct or Solar Pro 4?

Solar Pro 4, with 524k tokens against 131k.

Head to head · tested 27 Oct 2026

Llama 3.3 70B Instruct vs Solar Pro 4: accuracy, speed and price

Similar accuracy; Llama 3.3 70B Instruct costs less per question.

MetaLlama 3.3 70B Instruct42.5% score · #52$0.00053 per question42 tok/s

UpstageSolar Pro 445.0% score · #49$0.0018 per question91 tok/s

Verdict

Built from the measurements below

Accuracy is too close to call: Llama 3.3 70B Instruct scored 42.5% and Solar Pro 4 45.0% on the same 80 questions, a gap within what chance alone could produce.
Llama 3.3 70B Instruct is 3.4× cheaper per question as billed ($0.00053 vs $0.0018), reasoning tokens included.
Solar Pro 4 generates text 2.2× faster: 91 tokens per second against 42.
Solar Pro 4 starts answering sooner: 0.6 s to the first token, against 0.7 s for Llama 3.3 70B Instruct.
Solar Pro 4 accepts more context: 524k tokens against 131k.

Which should you choose?

Choose Llama 3.3 70B Instruct for the lower cost per correct answer ($0.0013 against $0.0041), shorter outputs (about 855 tokens per question against 2,952), open weights you can run yourself and more hosts to choose from on OpenRouter (9 against 1). Choose Solar Pro 4 for faster streaming, a quicker first token and a 524k-token context window. The widest subject gap is in humanities & social science: Llama 3.3 70B Instruct answered 9 of 9 correctly, Solar Pro 4 6 of 9. With so few questions per subject, treat this as a lead to test on your own prompts, not a result.

Accuracy gap -2.5 points (z = -0.32). 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	Llama 3.3 70B Instruct	Solar Pro 4	Edge
Verification scoreHigher is better	42.5%	45.0%	Too close to call
Cost per questionLower is better	$0.00053	$0.0018	Llama 3.3 70B Instruct
Output speedHigher is better	42	91	Solar Pro 4
Time to first tokenLower is better	0.7 s	0.6 s	Solar Pro 4
End-to-end response timeLower is better	8.8 s	8.3 s	Similar
Tokens per questionLower is better	855	2,952	Llama 3.3 70B Instruct
Context windowHigher is better	131k	524k	Solar Pro 4

Side by side

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

Every measure

Llama 3.3 70B Instruct first, Solar Pro 4 second

Verification scorehigher is better

Llama 3.3 70B Instruct42.5%

Solar Pro 445.0%

Cost per questionlower is better

Llama 3.3 70B Instruct$0.00053

Solar Pro 4$0.0018

Output speedhigher is better

Llama 3.3 70B Instruct42

Solar Pro 491

Time to first tokenlower is better

Llama 3.3 70B Instruct0.7 s

Solar Pro 40.6 s

End-to-end response timelower is better

Llama 3.3 70B Instruct8.8 s

Solar Pro 48.3 s

Tokens per questionlower is better

Llama 3.3 70B Instruct855

Solar Pro 42,952

Context windowhigher is better

Llama 3.3 70B Instruct131k

Solar Pro 4524k

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	Llama 3.3 70B Instruct	Solar Pro 4
Science	30	11/30	18/30
Engineering	15	2/15	1/15
Medicine	11	6/11	5/11
Economics	9	5/9	5/9
Law	6	1/6	1/6
Humanities & social science	9	9/9	6/9
SuperGPQA dataset	50	9/50	14/50
MMLU-Pro dataset	30	25/30	22/30

Specifications and pricing

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

Specification	Llama 3.3 70B Instruct	Solar Pro 4
Creator	Meta	Upstage
Released	6 Dec 2024	10 Aug 2026
Weights	Open weights	—
Reasoning	No	Yes
Input	text	text
Output	text	text
Context window	131k tokens	524k tokens
Knowledge cutoff	31 Dec 2023	—
List price in / out per 1M	$0.1 / $0.32	$0.15 / $0.6
Blended price per 1M (3:1)	$0.16	$0.26
Cheapest host	DeepInfra · $0.1 / $0.32	Upstage · $0.15 / $0.6
Hosts on OpenRouter	9	1
Last tested	26 Oct 2026	26 Oct 2026

Compare any two models →

Llama 3.3 70B Instruct vs Solar Pro 4: frequently asked questions

Is Llama 3.3 70B Instruct better than Solar Pro 4?: On accuracy they are statistically tied: Llama 3.3 70B Instruct scored 42.5% and Solar Pro 4 45.0% on the same 80 questions from open datasets. Similar accuracy; Llama 3.3 70B Instruct costs less per question.
Which is cheaper, Llama 3.3 70B Instruct or Solar Pro 4?: Llama 3.3 70B Instruct is cheaper: $0.00053 per question as billed, against $0.0018. List prices: Llama 3.3 70B Instruct $0.1 in / $0.32 out, Solar Pro 4 $0.15 in / $0.6 out per million tokens.
Which is faster, Llama 3.3 70B Instruct or Solar Pro 4?: Solar Pro 4 is faster at 91 output tokens per second, against 42. Time to first token: 0.7 s for Llama 3.3 70B Instruct, 0.6 s for Solar Pro 4.
Which has the larger context window, Llama 3.3 70B Instruct or Solar Pro 4?: Solar Pro 4, with 524k tokens against 131k.