API cost decision in 10 seconds

Qwen3.6 27B vs Qwen3.5 397B A17B

Pick Qwen3.6 27B when budget is the priority.

Pricing data updated: 2026-05-26T11:08:00Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen3.6 27B when budget is the priority.

On the standard 1M input plus 500K output workload, Qwen3.6 27B is estimated at $1.3 vs $1.56 for Qwen3.5 397B A17B, saving $0.26 (16.7% lower).

Cost-first pickQwen3.6 27B

Context-first pickBoth models

Sample savings$0.2616.7%

10x traffic gap$2.6

The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $2.6. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3.6 27B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Qwen3.6 27B	Qwen3.5 397B A17B
Input-heavy / RAG	5M input + 500K output	Qwen3.6 27B	$2.5	$3.12
Balanced workload	1M input + 1M output	Qwen3.6 27B	$2.3	$2.73
Output-heavy chatbot	1M input + 5M output	Qwen3.6 27B	$10.3	$12.09

Cheaper input Qwen3.6 27B $0.3 vs $0.39 / 1M

Qwen3.6 27B is $0.09 cheaper per 1M input tokens (23.1% lower; 1.3x difference).

Cheaper output Qwen3.6 27B $2 vs $2.34 / 1M

Qwen3.6 27B is $0.34 cheaper per 1M output tokens (14.5% lower; 1.17x difference).

Larger context Tie 262.14K vs 262.14K

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

Sample workload Qwen3.6 27B $1.3 vs $1.56

Qwen3.6 27B is $0.26 cheaper on the standard workload (16.7% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Qwen3.6 27B Calculating… Estimated API cost

Qwen3.5 397B A17B 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

Qwen3.6 27B has the lower input price; Qwen3.6 27B has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Qwen3.6 27B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.3 for Qwen3.6 27B and $1.56 for Qwen3.5 397B A17B.

Best Fit

Choose Qwen3.6 27B when you care most about lower input-token price, and lower output-token price.

Choose Qwen3.5 397B A17B 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, Qwen3.6 27B is estimated at $1.3 vs $1.56 for Qwen3.5 397B A17B, saving $0.26 (16.7% lower).
Qwen3.6 27B is $0.26 cheaper on the standard workload (16.7% lower).
Qwen3.6 27B is $0.09 cheaper per 1M input tokens (23.1% lower; 1.3x difference).
Qwen3.6 27B is $0.34 cheaper per 1M output tokens (14.5% lower; 1.17x difference).
Both models report the same context window at 262.14K tokens.

Head-to-Head Specs

Feature	Qwen3.6 27B (Qwen)	Qwen3.5 397B A17B (Qwen)
Input Price prompt tokens per 1M	$0.3	$0.39
Completion Price per 1M tokens	$2	$2.34
Sample Workload Cost 1M input + 500K output	$1.3	$1.56
Context Window	262.14K	262.14K
Release Date	2026-04-27	2026-02-16

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Qwen3.6 27B	On the standard 1M input plus 500K output workload, Qwen3.6 27B is estimated at $1.3 vs $1.56 for Qwen3.5 397B A17B, saving $0.26 (16.7% lower).
High-volume input processing	Qwen3.6 27B	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Qwen3.6 27B	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 Qwen3.6 27B when lower sample workload cost matters most: $0.
Qwen3 Coder 480B A35B (free) can replace Qwen3.6 27B when lower sample workload cost matters most: $0.
Qwen2.5 7B Instruct can replace Qwen3.6 27B when lower sample workload cost matters most: $0.09.
Qwen3.5-9B can replace Qwen3.6 27B 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.
Gemini 3.1 Flash Lite offers 1.05M context with $1 sample workload cost.
DeepSeek V4 Pro offers 1.05M context with $0.87 sample workload cost.

Popular competitors

No popular competitor is currently available.

Cheaper alternatives

Review low-cost models sorted by a standard 1M input plus 500K output workload.

Open cheapest models

Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

Open largest context models

Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

Open provider hubs

Qwen catalog

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

Open Qwen models

Qwen3.6 27B

Qwen3.6 27B is a dense 27-billion-parameter language model from the Qwen Team at Alibaba, released in April 2026. It features hybrid multimodal capabilities — accepting text, image, and video inputs...

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...