API cost decision in 10 seconds

Qwen3 235B A22B Thinking 2507 vs Llama 3.1 70B Instruct

Pick Llama 3.1 70B Instruct for lower cost; pick Qwen3 235B A22B Thinking 2507 only if the larger context window matters more.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-28T03:07:35Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Llama 3.1 70B Instruct for lower cost; pick Qwen3 235B A22B Thinking 2507 only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $0.9 for Qwen3 235B A22B Thinking 2507, saving $0.3 (33.1% lower).

Cost-first pickLlama 3.1 70B Instruct

Context-first pickQwen3 235B A22B Thinking 2507

Sample savings$0.333.1%

10x traffic gap$2.97

Qwen3 235B A22B Thinking 2507 has more context, but Llama 3.1 70B Instruct saves $0.3 on the standard workload. At 10x that traffic, the same price gap is about $2.97. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Qwen3 235B A22B Thinking 2507, balanced workload favors Llama 3.1 70B Instruct, and output-heavy chatbot favors Llama 3.1 70B Instruct.

Workload shape	Token mix	Better pick	Qwen3 235B A22B Thinking 2507	Llama 3.1 70B Instruct
Input-heavy / RAG	5M input + 500K output	Qwen3 235B A22B Thinking 2507	$1.5	$2.2
Balanced workload	1M input + 1M output	Llama 3.1 70B Instruct	$1.64	$0.8
Output-heavy chatbot	1M input + 5M output	Llama 3.1 70B Instruct	$7.62	$2.4

Cheaper input Qwen3 235B A22B Thinking 2507 $0.1495 vs $0.4 / 1M

Qwen3 235B A22B Thinking 2507 is $0.25 cheaper per 1M input tokens (62.6% lower; 2.68x difference).

Cheaper output Llama 3.1 70B Instruct $1.495 vs $0.4 / 1M

Llama 3.1 70B Instruct is $1.1 cheaper per 1M output tokens (73.2% lower; 3.74x difference).

Larger context Qwen3 235B A22B Thinking 2507 262.14K vs 131.07K

Qwen3 235B A22B Thinking 2507 has 131.07K more context (2x larger).

Sample workload Llama 3.1 70B Instruct $0.9 vs $0.6

Llama 3.1 70B Instruct is $0.3 cheaper on the standard workload (33.1% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Qwen3 235B A22B Thinking 2507 Calculating… Estimated API cost

Llama 3.1 70B Instruct Calculating… Estimated API cost

Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

Qwen3 235B A22B Thinking 2507 has the lower input price; Llama 3.1 70B Instruct has the lower output price; Qwen3 235B A22B Thinking 2507 offers the larger context window. For the 1M input plus 500K output sample, Llama 3.1 70B Instruct is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.9 for Qwen3 235B A22B Thinking 2507 and $0.6 for Llama 3.1 70B Instruct.

Best Fit

Choose Qwen3 235B A22B Thinking 2507 when you care most about lower input-token price, and larger context window.

Choose Llama 3.1 70B Instruct when you care most about lower output-token price.

Decision Notes

On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $0.9 for Qwen3 235B A22B Thinking 2507, saving $0.3 (33.1% lower).
Llama 3.1 70B Instruct is $0.3 cheaper on the standard workload (33.1% lower).
Qwen3 235B A22B Thinking 2507 is $0.25 cheaper per 1M input tokens (62.6% lower; 2.68x difference).
Llama 3.1 70B Instruct is $1.1 cheaper per 1M output tokens (73.2% lower; 3.74x difference).
Qwen3 235B A22B Thinking 2507 has 131.07K more context (2x larger).

Head-to-Head Specs

Feature	Qwen3 235B A22B Thinking 2507 (Qwen)	Llama 3.1 70B Instruct (Meta)
Input Price prompt tokens per 1M	$0.1495	$0.4
Completion Price per 1M tokens	$1.495	$0.4
Sample Workload Cost 1M input + 500K output	$0.9	$0.6
Context Window	262.14K	131.07K
Release Date	2025-07-25	2024-07-23
Popularity	#107	#142

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Llama 3.1 70B Instruct	On the standard 1M input plus 500K output workload, Llama 3.1 70B Instruct is estimated at $0.6 vs $0.9 for Qwen3 235B A22B Thinking 2507, saving $0.3 (33.1% lower).
High-volume input processing	Qwen3 235B A22B Thinking 2507	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Llama 3.1 70B Instruct	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Qwen3 235B A22B Thinking 2507	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

Qwen3 Next 80B A3B Instruct (free) can replace Qwen3 235B A22B Thinking 2507 when lower sample workload cost matters most: $0.
Qwen3 Coder 480B A35B (free) can replace Qwen3 235B A22B Thinking 2507 when lower sample workload cost matters most: $0.
Qwen2.5 7B Instruct can replace Qwen3 235B A22B Thinking 2507 when lower sample workload cost matters most: $0.09.
Qwen3.5-9B can replace Qwen3 235B A22B Thinking 2507 when lower sample workload cost matters most: $0.11.

Larger context near this budget

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.

Popular competitors

Hy3 preview · Tencent · #1
DeepSeek V4 Flash · DeepSeek · #2
Claude Opus 4.7 · Anthropic · #3
Claude Sonnet 4.6 · Anthropic · #4

Cheaper alternatives

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Larger context alternatives

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Provider catalogs

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Qwen catalog

Review all tracked Qwen models before deciding whether this matchup is the right shortlist.

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Meta catalog

Check other Meta models with comparable pricing, context, or release timing.

Open Meta models

Qwen3 235B A22B Thinking 2507

Qwen3-235B-A22B-Thinking-2507 is a high-performance, open-weight Mixture-of-Experts (MoE) language model optimized for complex reasoning tasks. It activates 22B of its 235B parameters per forward pass and natively supports up to 262,144...

Llama 3.1 70B Instruct

Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...