Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507

Comparison

As of August 25, 2026, Llama 3.2 3B Instruct is 99% cheaper per million tokens than Qwen3-235B-A22B-Thinking-2507. Llama 3.2 3B Instruct is $0.01 / $0.02 per million input/output tokens versus Qwen3-235B-A22B-Thinking-2507 at $0.30 / $3.00. Sources: https://llama.meta.com/ and https://bailian.console.aliyun.com/

Sources: Meta pricing (https://llama.meta.com/); Qwen pricing (https://bailian.console.aliyun.com/)

Better value

Llama 3.2 3B Instruct

Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507 comparison

Token pricing, specs, and benchmarks side by side

Shared benchmarks

Each bar is share of the current leader on that eval. Click a row to open the board.

Llama 3.2 3B InstructQwen3-235B-A22B-Thinking-2507

Score vs price

GPQA. Left is cheaper. Up is a higher score. The line is the best score you can buy at each price.

Best score at each priceLlama 3.2 3B InstructQwen3-235B-A22B-Thinking-2507

Metric

Llama 3.2 3B Instruct

Qwen3-235B-A22B-Thinking-2507

Provider

Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507: the bottom line

Llama 3.2 3B Instruct offers significantly lower pricing, while Qwen3-235B-A22B-Thinking-2507 leads on benchmark performance. Your choice depends on whether cost efficiency or raw capability matters more for your use case.

View Llama 3.2 3B Instruct details View Qwen3-235B-A22B-Thinking-2507 details

Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507 FAQ

Which is cheaper, Llama 3.2 3B Instruct or Qwen3-235B-A22B-Thinking-2507?

As of August 25, 2026, Llama 3.2 3B Instruct is 99% cheaper on blended LLM API pricing. Llama 3.2 3B Instruct costs $0.01 per million input tokens and $0.02 per million output tokens ($0.03 blended 1M-in + 1M-out). Qwen3-235B-A22B-Thinking-2507 costs $0.30 / $3.00 per million tokens ($3.30 blended). Sources: https://llama.meta.com/ and https://bailian.console.aliyun.com/. The cheapest LLM for your app still depends on how many output tokens you generate.

How much does Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507 cost per million tokens?

Llama 3.2 3B Instruct Meta API pricing is $0.01 input and $0.02 output per million tokens via Meta. Qwen3-235B-A22B-Thinking-2507 Qwen API pricing is $0.30 input and $3.00 output per million tokens via Qwen. Use those four numbers, not ChatGPT Plus or Claude Pro subscription prices, when you are comparing APIs.

Which is better for coding, Llama 3.2 3B Instruct or Qwen3-235B-A22B-Thinking-2507?

Neither Llama 3.2 3B Instruct nor Qwen3-235B-A22B-Thinking-2507 has a published SWE-bench or LiveCodeBench score on this page yet. Use the comparison table for the evals that do exist.

What is the context window for Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507?

Llama 3.2 3B Instruct supports a 128K token context window, while Qwen3-235B-A22B-Thinking-2507 supports 262K tokens. Qwen3-235B-A22B-Thinking-2507 offers a larger context window. Filling a larger window bills more input tokens, so the cheaper-per-million model can still cost more on long documents.

Which model performs better on benchmarks, Llama 3.2 3B Instruct or Qwen3-235B-A22B-Thinking-2507?

Qwen3-235B-A22B-Thinking-2507 leads on 2 of 2 shared benchmarks versus Llama 3.2 3B Instruct's 0 wins. Check the comparison table for GPQA Diamond, SWE-bench, MMLU, HLE, and the other evals we track. Token price and benchmark score together are the usual LLM comparison, not either number alone.

Is Llama 3.2 3B Instruct or Qwen3-235B-A22B-Thinking-2507 better for production use?

Both Llama 3.2 3B Instruct and Qwen3-235B-A22B-Thinking-2507 are production API models. For cost-sensitive production traffic, Llama 3.2 3B Instruct has better economics on the blended 1M-in + 1M-out scale. For maximum capability, weight the benchmark table for your domain. Many production stacks route cheap models for drafts and a frontier model for the hard turn, which is usually cheaper than sending everything to the expensive API.

Can I switch between Llama 3.2 3B Instruct and Qwen3-235B-A22B-Thinking-2507 in my app?

Yes. Call Llama 3.2 3B Instruct through Meta and Qwen3-235B-A22B-Thinking-2507 through Qwen with separate API keys, or through a gateway that already wraps both. Keep prompts in tokens, not characters, when you estimate the invoice. AnotherWrapper templates can swap providers without rewriting auth and billing.

How accurate is this Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507 pricing data?

List rates are the latest published Meta API pricing and Qwen API pricing, quoted per million tokens. Official rate sheets: https://llama.meta.com/ and https://bailian.console.aliyun.com/. Prompt caching, batch APIs, and committed-use discounts can change the invoice. Benchmark scores are from official publications and independent evals, updated as new numbers land.

What is the output token limit for Llama 3.2 3B Instruct and Qwen3-235B-A22B-Thinking-2507?

Llama 3.2 3B Instruct supports up to 128K output tokens per request, while Qwen3-235B-A22B-Thinking-2507 supports up to 131K output tokens. Output tokens are usually the expensive half of API pricing, so a higher max output cap is a capability, not a discount.

Which model has better throughput, Llama 3.2 3B Instruct or Qwen3-235B-A22B-Thinking-2507?

Llama 3.2 3B Instruct has a measured throughput of approximately 171.5 tokens/second. Throughput data for Qwen3-235B-A22B-Thinking-2507 is not yet available. Throughput (tokens per second) and time-to-first-token are why two models with the same per-million-token price can still feel different in chat and agents.

How do I switch the models in this Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507 comparison?

Use the model pickers at the top of this LLM comparison. Search any model in the index and the URL updates. Open Llama 3.2 3B Instruct or Qwen3-235B-A22B-Thinking-2507 from the sidebar for the single-model API pricing page, or go back to the LLM pricing table to sort by cheapest blended cost.

Llama 3.2 3B Instruct vs Qwen3-235B-A22B-Thinking-2507 pricing

This comparison covers API pricing, context window, throughput, and benchmark scores. Llama 3.2 3B Instruct costs $0.01/M input and $0.02/M output. Qwen3-235B-A22B-Thinking-2507 costs $0.30/M input and $3.00/M output.

Rank both on the LLM leaderboard, SWE-bench, and Humanity's Last Exam.