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Model comparison · Updated 1 Sep 2026

Llama 3.1 70B Instruct vs Qwen2.5 72B Instruct

Qwen2.5 72B Instruct is about 1.1× cheaper on input ($0.36 against $0.40 per 1M tokens). Llama 3.1 70B Instruct has the larger context window (131K against 33K tokens). For a support chatbot at 10,000 chats a day, the standard-tier bill is about $216 a month for Llama 3.1 70B Instruct and $198 for Qwen2.5 72B Instruct.

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ModelsAtlas. “Llama 3.1 70B Instruct vs Qwen2.5 72B Instruct”. Retrieved 1 Sep 2026. https://modelsatlas.com/compare/meta/llama-3-1-70b-instruct/vs/qwen/2-5-72b-instruct

Model A

Llama 3.1 70B Instruct

by Meta · weights not marked open · GRIDD3

Input / 1M
$0.40
observed We measured
Source
Our catalogue
Retrieved
17 Aug 2026
Output / 1M$0.40
Context131K
vs

Model B

Qwen2.5 72B Instruct

by Qwen (Alibaba) · weights not marked open · GRIDD2

Input / 1M
$0.36
observed We measured
Source
Our catalogue
Retrieved
17 Aug 2026
Output / 1M$0.40
Context33K

Key numbers

Standard tier · highlighted = better

Llama 3.1 70B Instruct
Qwen2.5 72B Instruct
Input / 1M tokens
$0.40
$0.36
Output / 1M tokens
$0.40
$0.40
Batch input / output
Not listed
Not listed
Context window
131,072
32,768
Input types
Not disclosed
Not disclosed
Weights
Not marked open
Not marked open
Tiers listed
standard
standard
Prices checked
2026-08-17
2026-09-01

What it costs for real workloads

Monthly, standard tier, 30 days

Support chatbot10k chats/day · 1.5k in, 300 out
$216/mo
$198/mo
RAG over documents2k queries/day · 12k in, 500 out
$300/mo
$271/mo
Coding agent300 tasks/day · 60k in, 8k out
$245/mo
$223/mo

Llama 3.1 70B Instruct   Qwen2.5 72B Instruct · Derived from the standard-tier prices above, input and output tokens per request as stated, 30 days. Excludes caching discounts and batch. Try your own numbers.

On the atlas

Price band (A–H) × context band (1–6)

1 square apart. Qwen2.5 72B Instruct (D2) sits 1 context band smaller than Llama 3.1 70B Instruct (D3).

Same square as Llama 3.1 70B Instruct: Codestral 2508 ($0.30), Command A+ ($0.30), MiniMax M2.1 ($0.30). Same square as Qwen2.5 72B Instruct: MiniMax M2-her ($0.30), Nano Banana (Gemini 2.5 Flash Image) ($0.30), Mistral Small 3.1 24B ($0.35). Open D3 · Open D2

AFreeB<$0.10C$0.10–0.30D$0.30–1E$1–3F$3–10G$10–30H$30+1<32K232–128K3128–256K4256K–1M51M6>1MINPUT PRICE PER 1M TOKENS →CONTEXT WINDOW ↑ · position within a square follows the real valueMistral Medium 3 · D3Mistral Medium 3.1 · D3R1 0528 · D3Nano Banana 2 (Gemini 3.1 Flash Image) · D3Command A+ · D3Muse Glimmer 30B · D3Mistral Small 3.1 24B · D2Nano Banana (Gemini 2.5 Flash Image) · D2MiniMax M2-her · D2Qwen2.5 Coder 32B Instruct · D2Qwen2.5 VL 72B Instruct · D2Llama 3.1 70B InstructLlama 3.1 70B InstructQwen2.5 72B InstructQwen2.5 72B Instruct
Llama 3.1 70B InstructQwen2.5 72B InstructNearest neighboursOpen weights
View the map as a table (2 squares)

Capabilities side by side

Only what our records list

Llama 3.1 70B Instruct
Qwen2.5 72B Instruct
Vision input
Not disclosed
Not disclosed
Audio input
Not disclosed
Not disclosed
Open weights
Not marked open
Not marked open
Batch tier
Not listed
Not listed
Free tier
Not listed
Not listed
Thinking tier
Not listed
Not listed

Neither record lists input types, so we do not claim any.

Which should you choose?

Editorial

Choose Llama 3.1 70B Instruct if…

  • your prompts are long: it takes 131,072 tokens against 32,768

Choose Qwen2.5 72B Instruct if…

  • you pay by the token: it costs $0.36 per 1M input against $0.40

Each reason is a fact from the tables above. Picking between them is our judgement, and we do not benchmark quality: price and context are what we can measure, so test both on your own prompts before you commit.

Questions

Is Llama 3.1 70B Instruct better than Qwen2.5 72B Instruct?
We do not benchmark quality, so we cannot say. On the recorded numbers: Qwen2.5 72B Instruct is about 1.1× cheaper on input ($0.36 against $0.40 per 1M tokens). Llama 3.1 70B Instruct has the larger context window (131K against 33K tokens). For a support chatbot at 10,000 chats a day, the standard-tier bill is about $216 a month for Llama 3.1 70B Instruct and $198 for Qwen2.5 72B Instruct. Which is better for you depends on your task; test both on your own prompts.
Which is cheaper, Llama 3.1 70B Instruct or Qwen2.5 72B Instruct?
Qwen2.5 72B Instruct: $0.36 against $0.40 per 1M input tokens, and $0.40 against $0.40 per 1M output, on standard pricing.
How much does each cost per 1M tokens?
Llama 3.1 70B Instruct: $0.40 input and $0.40 output. Qwen2.5 72B Instruct: $0.36 input and $0.40 output. Standard tier, USD.
Which has the larger context window?
Llama 3.1 70B Instruct, with 131,072 tokens. Qwen2.5 72B Instruct has 32,768 tokens.
Do both offer batch pricing?
Neither lists a batch tier in our catalogue.
Can both read images or audio?
Input types recorded for Llama 3.1 70B Instruct: none recorded. For Qwen2.5 72B Instruct: none recorded. Where a record lists none we say so rather than guess; check each vendor's documentation before relying on a capability.
Is either model open-weight?
Llama 3.1 70B Instruct: not marked open-weight in our records. Qwen2.5 72B Instruct: not marked open-weight in our records.
What would each cost for a support chatbot?
At 10,000 chats a day, 1,500 input and 300 output tokens each, 30 days, standard tier: about $216 a month for Llama 3.1 70B Instruct and $198 for Qwen2.5 72B Instruct. This is our calculation from the listed prices, not a quote.

About the two models

Llama 3.1 70B Instruct

By Meta. $0.40 input and $0.40 output per 1M tokens, 131K context, atlas square D3. Tiers listed: standard.

Full specs & pricing →

Qwen2.5 72B Instruct

By Qwen (Alibaba). $0.36 input and $0.40 output per 1M tokens, 33K context, atlas square D2. Tiers listed: standard.

Full specs & pricing →

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