API cost decision in 10 seconds

Qwen3.5 397B A17B vs R1 0528

Pick Qwen3.5 397B A17B when budget and context both matter.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T18:08:02Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen3.5 397B A17B when budget and context both matter.

On the standard 1M input plus 500K output workload, Qwen3.5 397B A17B is estimated at $1.56 vs $1.57 for R1 0528, saving $0.01 (1% lower).

Cost-first pickQwen3.5 397B A17B

Context-first pickQwen3.5 397B A17B

Sample savings$0.011%

10x traffic gap$0.15

Qwen3.5 397B A17B is cheaper on the standard workload and also has the larger context window. At 10x that traffic, the same price gap is about $0.15. 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 Qwen3.5 397B A17B, balanced workload favors R1 0528, and output-heavy chatbot favors R1 0528.

Workload shape	Token mix	Better pick	Qwen3.5 397B A17B	R1 0528
Input-heavy / RAG	5M input + 500K output	Qwen3.5 397B A17B	$3.12	$3.58
Balanced workload	1M input + 1M output	R1 0528	$2.73	$2.65
Output-heavy chatbot	1M input + 5M output	R1 0528	$12.09	$11.25

Cheaper input Qwen3.5 397B A17B $0.39 vs $0.5 / 1M

Qwen3.5 397B A17B is $0.11 cheaper per 1M input tokens (22% lower; 1.28x difference).

Cheaper output R1 0528 $2.34 vs $2.15 / 1M

R1 0528 is $0.19 cheaper per 1M output tokens (8.1% lower; 1.09x difference).

Larger context Qwen3.5 397B A17B 262.14K vs 163.84K

Qwen3.5 397B A17B has 98.3K more context (1.6x larger).

Sample workload Qwen3.5 397B A17B $1.56 vs $1.57

Qwen3.5 397B A17B is $0.01 cheaper on the standard workload (1% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Qwen3.5 397B A17B Calculating… Estimated API cost

R1 0528 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

Qwen3.5 397B A17B has the lower input price; R1 0528 has the lower output price; Qwen3.5 397B A17B offers the larger context window. For the 1M input plus 500K output sample, Qwen3.5 397B A17B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.56 for Qwen3.5 397B A17B and $1.57 for R1 0528.

Best Fit

Choose Qwen3.5 397B A17B when you care most about lower input-token price, and larger context window.

Choose R1 0528 when you care most about lower output-token price.

Decision Notes

On the standard 1M input plus 500K output workload, Qwen3.5 397B A17B is estimated at $1.56 vs $1.57 for R1 0528, saving $0.01 (1% lower).
Qwen3.5 397B A17B is $0.01 cheaper on the standard workload (1% lower).
Qwen3.5 397B A17B is $0.11 cheaper per 1M input tokens (22% lower; 1.28x difference).
R1 0528 is $0.19 cheaper per 1M output tokens (8.1% lower; 1.09x difference).
Qwen3.5 397B A17B has 98.3K more context (1.6x larger).

Head-to-Head Specs

Feature	Qwen3.5 397B A17B (Qwen)	R1 0528 (DeepSeek)
Input Price prompt tokens per 1M	$0.39	$0.5
Completion Price per 1M tokens	$2.34	$2.15
Sample Workload Cost 1M input + 500K output	$1.56	$1.57
Context Window	262.14K	163.84K
Release Date	2026-02-16	2025-05-28
Popularity	#53	#106

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Qwen3.5 397B A17B	On the standard 1M input plus 500K output workload, Qwen3.5 397B A17B is estimated at $1.56 vs $1.57 for R1 0528, saving $0.01 (1% lower).
High-volume input processing	Qwen3.5 397B A17B	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	R1 0528	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Qwen3.5 397B A17B	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 Qwen3.5 397B A17B when lower sample workload cost matters most: $0.
Qwen3 Coder 480B A35B (free) can replace Qwen3.5 397B A17B when lower sample workload cost matters most: $0.
Qwen2.5 7B Instruct can replace Qwen3.5 397B A17B when lower sample workload cost matters most: $0.09.
Qwen3.5-9B can replace Qwen3.5 397B A17B 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

DeepSeek V4 Flash · DeepSeek · #1
Hy3 preview · Tencent · #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

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DeepSeek catalog

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Qwen3.5 397B A17B

The Qwen3.5 series 397B-A17B native vision-language model is built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. It delivers...

R1 0528

May 28th update to the [original DeepSeek R1](/deepseek/deepseek-r1) Performance on par with [OpenAI o1](/openai/o1), but open-sourced and with fully open reasoning tokens. It's 671B parameters in size, with 37B active...