AI model comparison

Qwen3 32B vs Llama 3.3 70B Instruct

Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.

Qwen3-32B is a dense 32.8B parameter causal language model from the Qwen3 series, optimized for both complex reasoning and efficient dialogue.

Input / 1M
$0.08
Output / 1M
$0.28
Context
131K

The Meta Llama 3.3 multilingual large language model (LLM) is a pretrained and instruction tuned generative model in 70B (text in/text out).

Input / 1M
$0.10
Output / 1M
$0.32
Context
131K

At a glance

Quick verdict

How the two models stack up on the things people ask about most.

Lower price

qwen logo

Qwen3 32B

1.2x cheaper for a typical chat

Higher intelligence score

meta-llama logo

Llama 3.3 70B Instruct

7.7 vs 7.3 on Artificial Analysis

Larger context window

Tie

131K vs 131K tokens

Newer release

qwen logo

Qwen3 32B

Released April 28, 2025

Benchmarks

Benchmark scores

Independent scores from Artificial Analysis. Higher is better.

Intelligence index

qwen logoQwen3 32B7.3
meta-llama logoLlama 3.3 70B Instruct7.7

Coding index

qwen logoQwen3 32BNot available
meta-llama logoLlama 3.3 70B Instruct11.9

Agentic index

qwen logoQwen3 32BNot available
meta-llama logoLlama 3.3 70B InstructNot available

Pricing

Qwen3 32B vs Llama 3.3 70B Instruct API pricing

Per-token API rates. Cheaper option highlighted.

Metricqwen logoQwen3 32Bmeta-llama logoLlama 3.3 70B Instruct
Input tokensPer 1M tokens$0.08$0.10
Output tokensPer 1M tokens$0.28$0.32
Cached input (read)Per 1M tokensNot availableNot available
Cache writePer 1M tokensNot availableNot available

What it costs in practice

Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.

Chat message

2K in, 500 out

qwen logoQwen3 32B$0.30
meta-llama logoLlama 3.3 70B Instruct$0.36

Coding task

30K in, 4K out

qwen logoQwen3 32B$3.52
meta-llama logoLlama 3.3 70B Instruct$4.28

Long document summary

150K in, 2K out

qwen logoQwen3 32B$12.56
meta-llama logoLlama 3.3 70B Instruct$15.64

Specs

Context window and capabilities

How much each model can read, how much it can write, and what it accepts as input.

Metricqwen logoQwen3 32Bmeta-llama logoLlama 3.3 70B Instruct
Context window131K tokens131K tokens
Max output16K tokens16K tokens
Input typesTextText
Output typesTextText
Reasoning effort levelsNot availableNot available
Default reasoning effortNot availableNot available
Release dateApril 28, 2025December 6, 2024

Features

Supported features

API features available for each model.

Metricqwen logoQwen3 32Bmeta-llama logoLlama 3.3 70B Instruct
Tool callingSupportedSupported
Structured outputsSupportedSupported
JSON modeSupportedSupported
ReasoningSupportedNot supported
TemperatureSupportedSupported
Stop sequencesSupportedSupported
Deterministic seedSupportedSupported
Verbosity controlNot supportedNot supported

Our take

Qwen3 32B is 1.2x cheaper for a typical chat. Llama 3.3 70B Instruct scores higher on the Artificial Analysis Intelligence Index (7.7 vs 7.3). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.

FAQ

Frequently asked questions

Is Qwen3 32B or Llama 3.3 70B Instruct cheaper?

Qwen3 32B is cheaper for a typical chat (2K input tokens and 500 output tokens). Qwen3 32B costs $0.08 per 1M input tokens and $0.28 per 1M output tokens, while Llama 3.3 70B Instruct costs $0.10 per 1M input tokens and $0.32 per 1M output tokens.

Which has a bigger context window, Qwen3 32B or Llama 3.3 70B Instruct?

Qwen3 32B supports up to 131K tokens of context, compared with 131K for Llama 3.3 70B Instruct.

Is Qwen3 32B smarter than Llama 3.3 70B Instruct?

On the Artificial Analysis Intelligence Index, Qwen3 32B scores 7.3 and Llama 3.3 70B Instruct scores 7.7, putting Llama 3.3 70B Instruct ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.

Can I use Qwen3 32B and Llama 3.3 70B Instruct at the same time?

Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see Qwen3 32B and Llama 3.3 70B Instruct answer side by side and keep the better response.

qwen logometa-llama logo

Why choose? Ask both.

Send one prompt to Qwen3 32B and Llama 3.3 70B Instruct at the same time. Compare the answers side by side and keep the best one.