API cost decision in 10 seconds

Qwen3 235B A22B Instruct 2507 vs Mistral Large 3 2512

Pick Qwen3 235B A22B Instruct 2507 when budget is the priority.

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 Qwen3 235B A22B Instruct 2507 when budget is the priority.

On the standard 1M input plus 500K output workload, Qwen3 235B A22B Instruct 2507 is estimated at $0.12 vs $1.25 for Mistral Large 3 2512, saving $1.13 (90.3% lower).

Cost-first pickQwen3 235B A22B Instruct 2507

Context-first pickBoth models

Sample savings$1.1390.3%

10x traffic gap$11.29

The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $11.29. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3 235B A22B Instruct 2507 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Qwen3 235B A22B Instruct 2507	Mistral Large 3 2512
Input-heavy / RAG	5M input + 500K output	Qwen3 235B A22B Instruct 2507	$0.4	$3.25
Balanced workload	1M input + 1M output	Qwen3 235B A22B Instruct 2507	$0.17	$2
Output-heavy chatbot	1M input + 5M output	Qwen3 235B A22B Instruct 2507	$0.57	$8

Cheaper input Qwen3 235B A22B Instruct 2507 $0.071 vs $0.5 / 1M

Qwen3 235B A22B Instruct 2507 is $0.43 cheaper per 1M input tokens (85.8% lower; 7.04x difference).

Cheaper output Qwen3 235B A22B Instruct 2507 $0.1 vs $1.5 / 1M

Qwen3 235B A22B Instruct 2507 is $1.4 cheaper per 1M output tokens (93.3% lower; 15x difference).

Larger context Tie 262.14K vs 262.14K

Both models report the same context window at 262.14K tokens.

Sample workload Qwen3 235B A22B Instruct 2507 $0.12 vs $1.25

Qwen3 235B A22B Instruct 2507 is $1.13 cheaper on the standard workload (90.3% 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 Instruct 2507 Calculating… Estimated API cost

Mistral Large 3 2512 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 Instruct 2507 has the lower input price; Qwen3 235B A22B Instruct 2507 has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3 235B A22B Instruct 2507 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.12 for Qwen3 235B A22B Instruct 2507 and $1.25 for Mistral Large 3 2512.

Best Fit

Choose Qwen3 235B A22B Instruct 2507 when you care most about lower input-token price, and lower output-token price.

Choose Mistral Large 3 2512 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes

On the standard 1M input plus 500K output workload, Qwen3 235B A22B Instruct 2507 is estimated at $0.12 vs $1.25 for Mistral Large 3 2512, saving $1.13 (90.3% lower).
Qwen3 235B A22B Instruct 2507 is $1.13 cheaper on the standard workload (90.3% lower).
Qwen3 235B A22B Instruct 2507 is $0.43 cheaper per 1M input tokens (85.8% lower; 7.04x difference).
Qwen3 235B A22B Instruct 2507 is $1.4 cheaper per 1M output tokens (93.3% lower; 15x difference).
Both models report the same context window at 262.14K tokens.

Head-to-Head Specs

Feature	Qwen3 235B A22B Instruct 2507 (Qwen)	Mistral Large 3 2512 (Mistral)
Input Price prompt tokens per 1M	$0.071	$0.5
Completion Price per 1M tokens	$0.1	$1.5
Sample Workload Cost 1M input + 500K output	$0.12	$1.25
Context Window	262.14K	262.14K
Release Date	2025-07-21	2025-12-01
Popularity	#42	#114

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Qwen3 235B A22B Instruct 2507	On the standard 1M input plus 500K output workload, Qwen3 235B A22B Instruct 2507 is estimated at $0.12 vs $1.25 for Mistral Large 3 2512, saving $1.13 (90.3% lower).
High-volume input processing	Qwen3 235B A22B Instruct 2507	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Qwen3 235B A22B Instruct 2507	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Tie	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 Instruct 2507 when lower sample workload cost matters most: $0.
Qwen3 Coder 480B A35B (free) can replace Qwen3 235B A22B Instruct 2507 when lower sample workload cost matters most: $0.
Qwen2.5 7B Instruct can replace Qwen3 235B A22B Instruct 2507 when lower sample workload cost matters most: $0.09.
Qwen3.5-9B can replace Qwen3 235B A22B Instruct 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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Qwen catalog

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Mistral catalog

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Qwen3 235B A22B Instruct 2507

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...

Mistral Large 3 2512

Mistral Large 3 2512 is Mistral’s most capable model to date, featuring a sparse mixture-of-experts architecture with 41B active parameters (675B total), and released under the Apache 2.0 license.