Can I run Llama 3.1 70B or Qwen3.5-27B cheaper on another provider?

Some models are available on inference providers like Together AI, Groq, and Fireworks AI at lower prices. Check each model's pricing page for the full provider comparison.

What is the context window difference between Llama 3.1 70B and Qwen3.5-27B?

Qwen3.5-27B has a larger context window at 262K tokens vs 128K. This matters for long documents, large codebases, and extended conversation histories.

Compare

Llama 3.1 70B vs Qwen3.5-27B

Pricing is only the shared seller matrix below. Best rates and catalog map are separate sections, so no chart is embedded in pricing. Open the calculator for the same workload on each side.

MetaLlama 3.1

Model

Llama 3.1 70B

Tool calling

Best $0.400 in · $0.400 out

Context window 128K

Pricing

AlibabaQwen

Model

Qwen3.5-27B

Image inputTool calling

Best $0.300 in · $2.40 out

Context window 262K

Pricing

Qwen3.5-27B is 25% cheaper on input. Llama 3.1 70B is 83% cheaper on output. The best choice depends on your input/output ratio.

Estimate cost

Pricing matrix

Shared sellers only. Each row is a host that lists both models. Dollar amounts are per 1M tokens. Lowest in each pair of columns is emphasized.

Provider	Llama 3.1 70B in	Llama 3.1 70B out	Qwen3.5-27B in	Qwen3.5-27B out
DeepInfra	$0.520	$0.750	N/A	N/A
Fireworks AI	$0.900	$0.900	N/A	N/A
Groq	$0.590	$0.790	N/A	N/A
Openrouter	$0.400	$0.400	$0.300	$2.40
Perplexity	$1.00	$1.00	N/A	N/A
Together AI	$0.880	$0.880	N/A	N/A
Vercel Ai Gateway	$0.720	$0.720	N/A	N/A

Best listed rates (this pair)

Same "best row in current pricing" logic as model pages: a compact view of the lowest input and output we show for each side. This is not the seller matrix.

Catalog map · Meta · Alibaba

Each chart uses real catalog rows that include both list input and list output ($/1M). Larger green dots are the models on this comparison page; accent dots are other active models from that provider.

Meta · input vs output

Scatter chart: X = input $/M, Y = output $/M. This page's models are labeled on the green dots; hover others for detail.

ListedoutputUSD/1M

One dot per catalog row that has both list prices. Green dots are labeled with the models on this page; hover any dot for name and prices. Upper-right means higher cost on both axes ($/1M).

Alibaba · input vs output

ListedoutputUSD/1M

One dot per catalog row that has both list prices. Green dots are labeled with the models on this page; hover any dot for name and prices. Upper-right means higher cost on both axes ($/1M).

Specifications

Each column header is the full model name. Tint marks the favorable value where we compute a winner.

Spec

Llama 3.1 70B

Qwen3.5-27B

Context window: 128,000 tokens; 262,144 tokens
Max output tokens: 4,096 tokens; 65,536 tokens
Vision: No; Yes
Function calling: Yes; Yes
Streaming: Yes; No
Release date: Jul 2024; Feb 2026

Cost calculator

Same requests, input tokens, and output tokens for both columns. Pick the provider row that matches how you buy.

Llama 3.1 70B

Qwen3.5-27B

Requests / day

Input tokens

Output tokens

Llama 3.1 70B

Monthly

$324

Annual

$3.9K

Qwen3.5-27B

Monthly

$450

Annual

$5.5K

Save $126/month with Llama 3.1 70B

When to pick which

Short takeaways: no cards, just the points. Validate with your own workloads.

Long-context tasks
Use Qwen3.5-27B. Its 262K context window handles large codebases and documents better than 128K.
High-volume text generation
Use Llama 3.1 70B. Output tokens are 83% cheaper, which compounds significantly at scale.
Long output (reports, code files)
Use Qwen3.5-27B. Its 65K max output limit reduces the need to split requests.

Frequently asked questions

Qwen3.5-27B is cheaper on input tokens, while Llama 3.1 70B is cheaper on output. The best choice depends on your input/output ratio.

More comparisons

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