API cost decision in 10 seconds

Mercury 2 vs Qwen3.5 397B A17B

Pick Mercury 2 for lower cost; pick Qwen3.5 397B A17B 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 Qwen3.5 397B A17B 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 $1.56 for Qwen3.5 397B A17B, saving $0.94 (59.9% lower).

Cost-first pickMercury 2
Context-first pickQwen3.5 397B A17B
Sample savings$0.9459.9%
10x traffic gap$9.35

Qwen3.5 397B A17B has more context, but Mercury 2 saves $0.94 on the standard workload. At 10x that traffic, the same price gap is about $9.35. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Mercury 2 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickMercury 2Qwen3.5 397B A17B
Input-heavy / RAG5M input + 500K outputMercury 2$1.62$3.12
Balanced workload1M input + 1M outputMercury 2$1$2.73
Output-heavy chatbot1M input + 5M outputMercury 2$4$12.09
Cheaper input Mercury 2 $0.25 vs $0.39 / 1M

Mercury 2 is $0.14 cheaper per 1M input tokens (35.9% lower; 1.56x difference).

Cheaper output Mercury 2 $0.75 vs $2.34 / 1M

Mercury 2 is $1.59 cheaper per 1M output tokens (67.9% lower; 3.12x difference).

Larger context Qwen3.5 397B A17B 128K vs 262.14K

Qwen3.5 397B A17B has 134.14K more context (2.05x larger).

Sample workload Mercury 2 $0.62 vs $1.56

Mercury 2 is $0.94 cheaper on the standard workload (59.9% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Mercury 2 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

Mercury 2 has the lower input price; Mercury 2 has the lower output price; Qwen3.5 397B A17B 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 $0.62 for Mercury 2 and $1.56 for Qwen3.5 397B A17B.

Best Fit

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

Choose Qwen3.5 397B A17B when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Mercury 2 is estimated at $0.62 vs $1.56 for Qwen3.5 397B A17B, saving $0.94 (59.9% lower).
  • Mercury 2 is $0.94 cheaper on the standard workload (59.9% lower).
  • Mercury 2 is $0.14 cheaper per 1M input tokens (35.9% lower; 1.56x difference).
  • Mercury 2 is $1.59 cheaper per 1M output tokens (67.9% lower; 3.12x difference).
  • Qwen3.5 397B A17B has 134.14K more context (2.05x larger).
Head-to-Head Specs
FeatureMercury 2
(Inception)
Qwen3.5 397B A17B
(Qwen)
Input Price
prompt tokens per 1M
$0.25$0.39
Completion Price
per 1M tokens
$0.75$2.34
Sample Workload Cost
1M input + 500K output
$0.62$1.56
Context Window128K262.14K
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 $1.56 for Qwen3.5 397B A17B, saving $0.94 (59.9% lower).
High-volume input processingMercury 2Lower 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 workQwen3.5 397B A17BA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Larger context near this budget

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

Inception catalog

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

Open Inception models

Qwen catalog

Check other Qwen models with comparable pricing, context, or release timing.

Open Qwen models
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...

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...