API cost decision in 10 seconds

Qwen3.6 27B vs Qwen3.5-122B-A10B

The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.

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

Budget verdict

The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.

Both models are estimated at $1.3 for the standard 1M input plus 500K output workload.

Cost-first pickTie

Context-first pickBoth models

Sample savings$00%

10x traffic gap$0

Context-window winner: Both models. Cost does not separate this pair on the standard workload, so the next decision point is context window and model behavior.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Qwen3.5-122B-A10B, balanced workload favors Qwen3.6 27B, and output-heavy chatbot favors Qwen3.6 27B.

Workload shape	Token mix	Better pick	Qwen3.6 27B	Qwen3.5-122B-A10B
Input-heavy / RAG	5M input + 500K output	Qwen3.5-122B-A10B	$2.5	$2.34
Balanced workload	1M input + 1M output	Qwen3.6 27B	$2.3	$2.34
Output-heavy chatbot	1M input + 5M output	Qwen3.6 27B	$10.3	$10.66

Cheaper input Qwen3.5-122B-A10B $0.3 vs $0.26 / 1M

Qwen3.5-122B-A10B is $0.04 cheaper per 1M input tokens (13.3% lower; 1.15x difference).

Cheaper output Qwen3.6 27B $2 vs $2.08 / 1M

Qwen3.6 27B is $0.08 cheaper per 1M output tokens (3.8% lower; 1.04x difference).

Larger context Tie 262.14K vs 262.14K

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

Sample workload Tie $1.3 vs $1.3

Both models have the same estimated cost for the standard 1M input plus 500K output workload: $1.3.

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

Qwen3.5-122B-A10B 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

Qwen3.5-122B-A10B 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, the standard workload cost is tied.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.3 for Qwen3.6 27B and $1.3 for Qwen3.5-122B-A10B.

Best Fit

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

Choose Qwen3.5-122B-A10B when you care most about lower input-token price.

Decision Notes

Both models are estimated at $1.3 for the standard 1M input plus 500K output workload.
Both models have the same estimated cost for the standard 1M input plus 500K output workload: $1.3.
Qwen3.5-122B-A10B is $0.04 cheaper per 1M input tokens (13.3% lower; 1.15x difference).
Qwen3.6 27B is $0.08 cheaper per 1M output tokens (3.8% lower; 1.04x difference).
Both models report the same context window at 262.14K tokens.

Head-to-Head Specs

Feature	Qwen3.6 27B (Qwen)	Qwen3.5-122B-A10B (Qwen)
Input Price prompt tokens per 1M	$0.3	$0.26
Completion Price per 1M tokens	$2	$2.08
Sample Workload Cost 1M input + 500K output	$1.3	$1.3
Context Window	262.14K	262.14K
Release Date	2026-04-27	2026-02-25

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Tie	Both models are estimated at $1.3 for the standard 1M input plus 500K output workload.
High-volume input processing	Qwen3.5-122B-A10B	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.

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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...

Qwen3.5-122B-A10B

The Qwen3.5 122B-A10B 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. In terms of...