API cost decision in 10 seconds

Qwen3.6 35B A3B vs Mercury 2

Pick Mercury 2 for lower cost; pick Qwen3.6 35B A3B only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Mercury 2 for lower cost; pick Qwen3.6 35B A3B only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Mercury 2 is estimated at $0.62 vs $0.65 for Qwen3.6 35B A3B, saving $0.03 (3.8% lower).

Cost-first pickMercury 2
Context-first pickQwen3.6 35B A3B
Sample savings$0.033.8%
10x traffic gap$0.25

Qwen3.6 35B A3B has more context, but Mercury 2 saves $0.03 on the standard workload. At 10x that traffic, the same price gap is about $0.25. 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 Qwen3.6 35B A3B, balanced workload favors Mercury 2, and output-heavy chatbot favors Mercury 2.

Workload shapeToken mixBetter pickQwen3.6 35B A3BMercury 2
Input-heavy / RAG5M input + 500K outputQwen3.6 35B A3B$1.25$1.62
Balanced workload1M input + 1M outputMercury 2$1.15$1
Output-heavy chatbot1M input + 5M outputMercury 2$5.15$4
Cheaper input Qwen3.6 35B A3B $0.15 vs $0.25 / 1M

Qwen3.6 35B A3B is $0.1 cheaper per 1M input tokens (40% lower; 1.67x difference).

Cheaper output Mercury 2 $1 vs $0.75 / 1M

Mercury 2 is $0.25 cheaper per 1M output tokens (25% lower; 1.33x difference).

Larger context Qwen3.6 35B A3B 262.14K vs 128K

Qwen3.6 35B A3B has 134.14K more context (2.05x larger).

Sample workload Mercury 2 $0.65 vs $0.62

Mercury 2 is $0.03 cheaper on the standard workload (3.8% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Qwen3.6 35B A3B Calculating… Estimated API cost
Mercury 2 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 35B A3B has the lower input price; Mercury 2 has the lower output price; Qwen3.6 35B A3B offers the larger context window. For the 1M input plus 500K output sample, Mercury 2 is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.65 for Qwen3.6 35B A3B and $0.62 for Mercury 2.

Best Fit

Choose Qwen3.6 35B A3B when you care most about lower input-token price, and larger context window.

Choose Mercury 2 when you care most about lower output-token price.

Decision Notes
  • On the standard 1M input plus 500K output workload, Mercury 2 is estimated at $0.62 vs $0.65 for Qwen3.6 35B A3B, saving $0.03 (3.8% lower).
  • Mercury 2 is $0.03 cheaper on the standard workload (3.8% lower).
  • Qwen3.6 35B A3B is $0.1 cheaper per 1M input tokens (40% lower; 1.67x difference).
  • Mercury 2 is $0.25 cheaper per 1M output tokens (25% lower; 1.33x difference).
  • Qwen3.6 35B A3B has 134.14K more context (2.05x larger).
Head-to-Head Specs
FeatureQwen3.6 35B A3B
(Qwen)
Mercury 2
(Inception)
Input Price
prompt tokens per 1M
$0.15$0.25
Completion Price
per 1M tokens
$1$0.75
Sample Workload Cost
1M input + 500K output
$0.65$0.62
Context Window262.14K128K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionMercury 2On the standard 1M input plus 500K output workload, Mercury 2 is estimated at $0.62 vs $0.65 for Qwen3.6 35B A3B, saving $0.03 (3.8% lower).
High-volume input processingQwen3.6 35B A3BLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsMercury 2Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workQwen3.6 35B A3BA larger context window leaves more room for retrieved passages, conversation history, or source files.

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Qwen catalog

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Inception catalog

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Qwen3.6 35B A3B

Qwen3.6-35B-A3B is an open-weight multimodal model from Alibaba Cloud with 35 billion total parameters and 3 billion active parameters per token. It uses a hybrid sparse mixture-of-experts architecture combining Gated...

Mercury 2

Mercury 2 is an extremely fast reasoning LLM, and the first reasoning diffusion LLM (dLLM). Instead of generating tokens sequentially, Mercury 2 produces and refines multiple tokens in parallel, achieving...