API cost decision in 10 seconds

Qwen3.5-122B-A10B vs GPT-5.1

Pick Qwen3.5-122B-A10B for lower cost; pick GPT-5.1 only if the larger context window matters more.

Pricing data updated:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen3.5-122B-A10B for lower cost; pick GPT-5.1 only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Qwen3.5-122B-A10B is estimated at $1.3 vs $6.25 for GPT-5.1, saving $4.95 (79.2% lower).

Cost-first pickQwen3.5-122B-A10B
Context-first pickGPT-5.1
Sample savings$4.9579.2%
10x traffic gap$49.5

GPT-5.1 has more context, but Qwen3.5-122B-A10B saves $4.95 on the standard workload. At 10x that traffic, the same price gap is about $49.5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3.5-122B-A10B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickQwen3.5-122B-A10BGPT-5.1
Input-heavy / RAG5M input + 500K outputQwen3.5-122B-A10B$2.34$11.25
Balanced workload1M input + 1M outputQwen3.5-122B-A10B$2.34$11.25
Output-heavy chatbot1M input + 5M outputQwen3.5-122B-A10B$10.66$51.25
Cheaper input Qwen3.5-122B-A10B $0.26 vs $1.25 / 1M

Qwen3.5-122B-A10B is $0.99 cheaper per 1M input tokens (79.2% lower; 4.81x difference).

Cheaper output Qwen3.5-122B-A10B $2.08 vs $10 / 1M

Qwen3.5-122B-A10B is $7.92 cheaper per 1M output tokens (79.2% lower; 4.81x difference).

Larger context GPT-5.1 262.14K vs 400K

GPT-5.1 has 137.86K more context (1.53x larger).

Sample workload Qwen3.5-122B-A10B $1.3 vs $6.25

Qwen3.5-122B-A10B is $4.95 cheaper on the standard workload (79.2% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Qwen3.5-122B-A10B Calculating… Estimated API cost
GPT-5.1 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; Qwen3.5-122B-A10B has the lower output price; GPT-5.1 offers the larger context window. For the 1M input plus 500K output sample, Qwen3.5-122B-A10B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $1.3 for Qwen3.5-122B-A10B and $6.25 for GPT-5.1.

Best Fit

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

Choose GPT-5.1 when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Qwen3.5-122B-A10B is estimated at $1.3 vs $6.25 for GPT-5.1, saving $4.95 (79.2% lower).
  • Qwen3.5-122B-A10B is $4.95 cheaper on the standard workload (79.2% lower).
  • Qwen3.5-122B-A10B is $0.99 cheaper per 1M input tokens (79.2% lower; 4.81x difference).
  • Qwen3.5-122B-A10B is $7.92 cheaper per 1M output tokens (79.2% lower; 4.81x difference).
  • GPT-5.1 has 137.86K more context (1.53x larger).
Head-to-Head Specs
FeatureQwen3.5-122B-A10B
(Qwen)
GPT-5.1
(OpenAI)
Input Price
prompt tokens per 1M
$0.26$1.25
Completion Price
per 1M tokens
$2.08$10
Sample Workload Cost
1M input + 500K output
$1.3$6.25
Context Window262.14K400K
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionQwen3.5-122B-A10BOn the standard 1M input plus 500K output workload, Qwen3.5-122B-A10B is estimated at $1.3 vs $6.25 for GPT-5.1, saving $4.95 (79.2% lower).
High-volume input processingQwen3.5-122B-A10BLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsQwen3.5-122B-A10BLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGPT-5.1A larger context window leaves more room for retrieved passages, conversation history, or source files.

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Provider catalogs

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Qwen catalog

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OpenAI catalog

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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...

GPT-5.1

GPT-5.1 is the latest frontier-grade model in the GPT-5 series, offering stronger general-purpose reasoning, improved instruction adherence, and a more natural conversational style compared to GPT-5. It uses adaptive reasoning...