API cost decision in 10 seconds

Mistral Nemo vs Qwen3 235B A22B Thinking 2507

Pick Mistral Nemo 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: 2026-05-26T19:08:13Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Mistral Nemo 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, Mistral Nemo is estimated at $0.04 vs $0.9 for Qwen3 235B A22B Thinking 2507, saving $0.86 (96.1% lower).

Cost-first pickMistral Nemo

Context-first pickQwen3 235B A22B Thinking 2507

Sample savings$0.8696.1%

10x traffic gap$8.62

Qwen3 235B A22B Thinking 2507 has more context, but Mistral Nemo saves $0.86 on the standard workload. At 10x that traffic, the same price gap is about $8.62. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Mistral Nemo stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Mistral Nemo	Qwen3 235B A22B Thinking 2507
Input-heavy / RAG	5M input + 500K output	Mistral Nemo	$0.12	$1.5
Balanced workload	1M input + 1M output	Mistral Nemo	$0.05	$1.64
Output-heavy chatbot	1M input + 5M output	Mistral Nemo	$0.17	$7.62

Cheaper input Mistral Nemo $0.02 vs $0.1495 / 1M

Mistral Nemo is $0.13 cheaper per 1M input tokens (86.6% lower; 7.47x difference).

Cheaper output Mistral Nemo $0.03 vs $1.495 / 1M

Mistral Nemo is $1.47 cheaper per 1M output tokens (98% lower; 49.8x difference).

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

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

Sample workload Mistral Nemo $0.04 vs $0.9

Mistral Nemo is $0.86 cheaper on the standard workload (96.1% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Mistral Nemo Calculating… Estimated API cost

Qwen3 235B A22B Thinking 2507 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

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

For a 1M input token plus 500K output token workload, the estimated API cost is $0.04 for Mistral Nemo and $0.9 for Qwen3 235B A22B Thinking 2507.

Best Fit

Choose Mistral Nemo when you care most about lower input-token price, and lower output-token price.

Choose Qwen3 235B A22B Thinking 2507 when you care most about larger context window.

Decision Notes

On the standard 1M input plus 500K output workload, Mistral Nemo is estimated at $0.04 vs $0.9 for Qwen3 235B A22B Thinking 2507, saving $0.86 (96.1% lower).
Mistral Nemo is $0.86 cheaper on the standard workload (96.1% lower).
Mistral Nemo is $0.13 cheaper per 1M input tokens (86.6% lower; 7.47x difference).
Mistral Nemo is $1.47 cheaper per 1M output tokens (98% lower; 49.8x difference).
Qwen3 235B A22B Thinking 2507 has 131.07K more context (2x larger).

Head-to-Head Specs

Feature	Mistral Nemo (Mistral)	Qwen3 235B A22B Thinking 2507 (Qwen)
Input Price prompt tokens per 1M	$0.02	$0.1495
Completion Price per 1M tokens	$0.03	$1.495
Sample Workload Cost 1M input + 500K output	$0.04	$0.9
Context Window	131.07K	262.14K
Release Date	2024-07-19	2025-07-25
Popularity	#34	#133

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Mistral Nemo	On the standard 1M input plus 500K output workload, Mistral Nemo is estimated at $0.04 vs $0.9 for Qwen3 235B A22B Thinking 2507, saving $0.86 (96.1% lower).
High-volume input processing	Mistral Nemo	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Mistral Nemo	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.

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Provider catalogs

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Mistral catalog

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Qwen catalog

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Open Qwen models

Mistral Nemo

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

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...