API cost decision in 10 seconds

Gemini 3.1 Pro Preview vs Qwen3 235B A22B Instruct 2507

Pick Qwen3 235B A22B Instruct 2507 for lower cost; pick Gemini 3.1 Pro Preview only if the larger context window matters more.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T18:08:02Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507 is estimated at $0.12 vs $8 for Gemini 3.1 Pro Preview, saving $7.88 (98.5% lower).

Cost-first pickQwen3 235B A22B Instruct 2507

Context-first pickGemini 3.1 Pro Preview

Sample savings$7.8898.5%

10x traffic gap$78.79

Gemini 3.1 Pro Preview has more context, but Qwen3 235B A22B Instruct 2507 saves $7.88 on the standard workload. At 10x that traffic, the same price gap is about $78.79. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Qwen3 235B A22B Instruct 2507 stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Gemini 3.1 Pro Preview	Qwen3 235B A22B Instruct 2507
Input-heavy / RAG	5M input + 500K output	Qwen3 235B A22B Instruct 2507	$16	$0.4
Balanced workload	1M input + 1M output	Qwen3 235B A22B Instruct 2507	$14	$0.17
Output-heavy chatbot	1M input + 5M output	Qwen3 235B A22B Instruct 2507	$62	$0.57

Cheaper input Qwen3 235B A22B Instruct 2507 $2 vs $0.071 / 1M

Qwen3 235B A22B Instruct 2507 is $1.93 cheaper per 1M input tokens (96.5% lower; 28.2x difference).

Cheaper output Qwen3 235B A22B Instruct 2507 $12 vs $0.1 / 1M

Qwen3 235B A22B Instruct 2507 is $11.9 cheaper per 1M output tokens (99.2% lower; 120x 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 235B A22B Instruct 2507 $8 vs $0.12

Qwen3 235B A22B Instruct 2507 is $7.88 cheaper on the standard workload (98.5% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Gemini 3.1 Pro Preview Calculating… Estimated API cost

Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507 has the lower input price; Qwen3 235B A22B Instruct 2507 has the lower output price; Gemini 3.1 Pro Preview offers the larger context window. For the 1M input plus 500K output sample, Qwen3 235B A22B Instruct 2507 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 $0.12 for Qwen3 235B A22B Instruct 2507.

Best Fit

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

Choose Qwen3 235B A22B Instruct 2507 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 235B A22B Instruct 2507 is estimated at $0.12 vs $8 for Gemini 3.1 Pro Preview, saving $7.88 (98.5% lower).
Qwen3 235B A22B Instruct 2507 is $7.88 cheaper on the standard workload (98.5% lower).
Qwen3 235B A22B Instruct 2507 is $1.93 cheaper per 1M input tokens (96.5% lower; 28.2x difference).
Qwen3 235B A22B Instruct 2507 is $11.9 cheaper per 1M output tokens (99.2% lower; 120x difference).
Gemini 3.1 Pro Preview has 786.43K more context (4x larger).

Head-to-Head Specs

Feature	Gemini 3.1 Pro Preview (Google)	Qwen3 235B A22B Instruct 2507 (Qwen)
Input Price prompt tokens per 1M	$2	$0.071
Completion Price per 1M tokens	$12	$0.1
Sample Workload Cost 1M input + 500K output	$8	$0.12
Context Window	1.05M	262.14K
Release Date	2026-02-19	2025-07-21
Popularity	#28	#42

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Qwen3 235B A22B Instruct 2507	On the standard 1M input plus 500K output workload, Qwen3 235B A22B Instruct 2507 is estimated at $0.12 vs $8 for Gemini 3.1 Pro Preview, saving $7.88 (98.5% lower).
High-volume input processing	Qwen3 235B A22B Instruct 2507	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Qwen3 235B A22B Instruct 2507	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Gemini 3.1 Pro Preview	A 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.

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Provider catalogs

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Google catalog

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Qwen catalog

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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 235B A22B Instruct 2507

Qwen3-235B-A22B-Instruct-2507 is a multilingual, instruction-tuned mixture-of-experts language model based on the Qwen3-235B architecture, with 22B active parameters per forward pass. It is optimized for general-purpose text generation, including instruction following,...