API cost decision in 10 seconds

Gemini 3.1 Pro Preview vs Qwen3.6 35B A3B

Pick Qwen3.6 35B A3B for lower cost; pick Gemini 3.1 Pro Preview 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 Qwen3.6 35B A3B for lower cost; pick Gemini 3.1 Pro Preview only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Qwen3.6 35B A3B is estimated at $0.65 vs $8 for Gemini 3.1 Pro Preview, saving $7.35 (91.9% lower).

Cost-first pickQwen3.6 35B A3B
Context-first pickGemini 3.1 Pro Preview
Sample savings$7.3591.9%
10x traffic gap$73.5

Gemini 3.1 Pro Preview has more context, but Qwen3.6 35B A3B saves $7.35 on the standard workload. At 10x that traffic, the same price gap is about $73.5. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3.6 35B A3B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickGemini 3.1 Pro PreviewQwen3.6 35B A3B
Input-heavy / RAG5M input + 500K outputQwen3.6 35B A3B$16$1.25
Balanced workload1M input + 1M outputQwen3.6 35B A3B$14$1.15
Output-heavy chatbot1M input + 5M outputQwen3.6 35B A3B$62$5.15
Cheaper input Qwen3.6 35B A3B $2 vs $0.15 / 1M

Qwen3.6 35B A3B is $1.85 cheaper per 1M input tokens (92.5% lower; 13.3x difference).

Cheaper output Qwen3.6 35B A3B $12 vs $1 / 1M

Qwen3.6 35B A3B is $11 cheaper per 1M output tokens (91.7% lower; 12x difference).

Larger context Gemini 3.1 Pro Preview 1.05M vs 262.14K

Gemini 3.1 Pro Preview has 786.43K more context (4x larger).

Sample workload Qwen3.6 35B A3B $8 vs $0.65

Qwen3.6 35B A3B is $7.35 cheaper on the standard workload (91.9% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Gemini 3.1 Pro Preview Calculating… Estimated API cost
Qwen3.6 35B A3B 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; Qwen3.6 35B A3B has the lower output price; Gemini 3.1 Pro Preview offers the larger context window. For the 1M input plus 500K output sample, Qwen3.6 35B A3B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $8 for Gemini 3.1 Pro Preview and $0.65 for Qwen3.6 35B A3B.

Best Fit

Choose Gemini 3.1 Pro Preview when you care most about larger context window.

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

Decision Notes
  • On the standard 1M input plus 500K output workload, Qwen3.6 35B A3B is estimated at $0.65 vs $8 for Gemini 3.1 Pro Preview, saving $7.35 (91.9% lower).
  • Qwen3.6 35B A3B is $7.35 cheaper on the standard workload (91.9% lower).
  • Qwen3.6 35B A3B is $1.85 cheaper per 1M input tokens (92.5% lower; 13.3x difference).
  • Qwen3.6 35B A3B is $11 cheaper per 1M output tokens (91.7% lower; 12x difference).
  • Gemini 3.1 Pro Preview has 786.43K more context (4x larger).
Head-to-Head Specs
FeatureGemini 3.1 Pro Preview
(Google)
Qwen3.6 35B A3B
(Qwen)
Input Price
prompt tokens per 1M
$2$0.15
Completion Price
per 1M tokens
$12$1
Sample Workload Cost
1M input + 500K output
$8$0.65
Context Window1.05M262.14K
Release Date
Popularity#28#76

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionQwen3.6 35B A3BOn the standard 1M input plus 500K output workload, Qwen3.6 35B A3B is estimated at $0.65 vs $8 for Gemini 3.1 Pro Preview, saving $7.35 (91.9% 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 chatbotsQwen3.6 35B A3BLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workGemini 3.1 Pro PreviewA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • Gemma 4 31B (free) can replace Gemini 3.1 Pro Preview when lower sample workload cost matters most: $0.
  • Gemma 4 26B A4B (free) can replace Gemini 3.1 Pro Preview when lower sample workload cost matters most: $0.
  • Lyria 3 Clip Preview can replace Gemini 3.1 Pro Preview when lower sample workload cost matters most: $0.
  • Lyria 3 Pro Preview can replace Gemini 3.1 Pro Preview when lower sample workload cost matters most: $0.
Larger context near this budget
  • Llama 4 Scout offers 10M context with $0.23 sample workload cost.
  • Grok 4.20 offers 2M context with $2.5 sample workload cost.
  • Grok 4.20 Multi-Agent offers 2M context with $5 sample workload cost.
  • GPT-5.4 offers 1.05M context with $10 sample workload cost.

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

Google catalog

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

Open Google models

Qwen catalog

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

Open Qwen models
Gemini 3.1 Pro Preview

Gemini 3.1 Pro Preview is Google’s frontier reasoning model, delivering enhanced software engineering performance, improved agentic reliability, and more efficient token usage across complex workflows. Building on the multimodal foundation...

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...