Compare

Llama 3.1 70B vs Qwen3 235b A22b Instruct 2507

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.

Meta

Model

Llama 3.1 70B

Tool calling

Best $0.400 in · $0.400 out

Context window 128K

Pricing
Alibaba

Model

Qwen3 235b A22b Instruct 2507

Tool calling

Best $0.090 in · $0.580 out

Context window 262K

Pricing

Qwen3 235b A22b Instruct 2507 is 77% cheaper on input. Llama 3.1 70B is 31% cheaper on output. The best choice depends on your input/output ratio.

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.

ProviderLlama 3.1 70B inLlama 3.1 70B outQwen3 235b A22b Instruct 2507 inQwen3 235b A22b Instruct 2507 out
DeepInfra$0.520$0.750$0.090$0.600
Fireworks AI$0.900$0.900$0.220$0.880
Groq$0.590$0.790N/AN/A
NovitaN/AN/A$0.090$0.580
Openrouter$0.400$0.400N/AN/A
Perplexity$1.00$1.00N/AN/A
ReplicateN/AN/A$0.264$1.06
Together AI$0.880$0.880N/AN/A
Vercel Ai Gateway$0.720$0.720N/AN/A
WandbN/AN/A$10000.00$10000.00

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 235b A22b Instruct 2507
Context window
128,000 tokens
262,144 tokens
Max output tokens
4,096 tokens
262,144 tokens
Vision
No
No
Function calling
Yes
Yes
Streaming
Yes
No
Release date
Jul 2024
N/A

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
Monthly
$324
Annual
$3.9K
Qwen3 235b A22b Instruct 2507
Monthly
$4.50M
Annual
$54.75M
Save $4.50M/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 235b A22b Instruct 2507. Its 262K context window handles large codebases and documents better than 128K.

  • High-volume text generation

    Use Llama 3.1 70B. Output tokens are 31% cheaper, which compounds significantly at scale.

  • Long output (reports, code files)

    Use Qwen3 235b A22b Instruct 2507. Its 262K max output limit reduces the need to split requests.

Frequently asked questions

Qwen3 235b A22b Instruct 2507 is cheaper on input tokens, while Llama 3.1 70B is cheaper on output. The best choice depends on your input/output ratio.

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