API cost decision in 10 seconds

NewLaguna XS.2 (free) vs Qwen3 VL 235B A22B Instruct

Pick Laguna XS.2 (free) for lower cost; pick Qwen3 VL 235B A22B Instruct 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 Laguna XS.2 (free) for lower cost; pick Qwen3 VL 235B A22B Instruct only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Laguna XS.2 (free) is estimated at $0 vs $0.64 for Qwen3 VL 235B A22B Instruct, saving $0.64 (100% lower).

Cost-first pickLaguna XS.2 (free)
Context-first pickQwen3 VL 235B A22B Instruct
Sample savings$0.64100%
10x traffic gap$6.4

Qwen3 VL 235B A22B Instruct has more context, but Laguna XS.2 (free) saves $0.64 on the standard workload. At 10x that traffic, the same price gap is about $6.4. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Laguna XS.2 (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickLaguna XS.2 (free)Qwen3 VL 235B A22B Instruct
Input-heavy / RAG5M input + 500K outputLaguna XS.2 (free)$0$1.44
Balanced workload1M input + 1M outputLaguna XS.2 (free)$0$1.08
Output-heavy chatbot1M input + 5M outputLaguna XS.2 (free)$0$4.6
Cheaper input Laguna XS.2 (free) $0 vs $0.2 / 1M

Laguna XS.2 (free) is free for input tokens while Qwen3 VL 235B A22B Instruct costs $0.2 per 1M tokens.

Cheaper output Laguna XS.2 (free) $0 vs $0.88 / 1M

Laguna XS.2 (free) is free for output tokens while Qwen3 VL 235B A22B Instruct costs $0.88 per 1M tokens.

Larger context Qwen3 VL 235B A22B Instruct 131.07K vs 262.14K

Qwen3 VL 235B A22B Instruct has 131.07K more context (2x larger).

Sample workload Laguna XS.2 (free) $0 vs $0.64

Laguna XS.2 (free) is free for the standard workload while the other model is estimated at $0.64.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
Laguna XS.2 (free) Calculating… Estimated API cost
Qwen3 VL 235B A22B Instruct 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

Laguna XS.2 (free) has the lower input price; Laguna XS.2 (free) has the lower output price; Qwen3 VL 235B A22B Instruct offers the larger context window. For the 1M input plus 500K output sample, Laguna XS.2 (free) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0 for Laguna XS.2 (free) and $0.64 for Qwen3 VL 235B A22B Instruct.

Best Fit

Choose Laguna XS.2 (free) when you care most about lower input-token price, and lower output-token price.

Choose Qwen3 VL 235B A22B Instruct when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, Laguna XS.2 (free) is estimated at $0 vs $0.64 for Qwen3 VL 235B A22B Instruct, saving $0.64 (100% lower).
  • Laguna XS.2 (free) is free for the standard workload while the other model is estimated at $0.64.
  • Laguna XS.2 (free) is free for input tokens while Qwen3 VL 235B A22B Instruct costs $0.2 per 1M tokens.
  • Laguna XS.2 (free) is free for output tokens while Qwen3 VL 235B A22B Instruct costs $0.88 per 1M tokens.
  • Qwen3 VL 235B A22B Instruct has 131.07K more context (2x larger).
Head-to-Head Specs
FeatureNewLaguna XS.2 (free)
(Poolside)
Qwen3 VL 235B A22B Instruct
(Qwen)
Input Price
prompt tokens per 1M
$0$0.2
Completion Price
per 1M tokens
$0$0.88
Sample Workload Cost
1M input + 500K output
$0$0.64
Context Window131.07K262.14K
Release Date
Popularity#56#103

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionLaguna XS.2 (free)On the standard 1M input plus 500K output workload, Laguna XS.2 (free) is estimated at $0 vs $0.64 for Qwen3 VL 235B A22B Instruct, saving $0.64 (100% lower).
High-volume input processingLaguna XS.2 (free)Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsLaguna XS.2 (free)Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workQwen3 VL 235B A22B InstructA larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps
  • Qwen3 Next 80B A3B Instruct (free) can replace Qwen3 VL 235B A22B Instruct when lower sample workload cost matters most: $0.
  • Qwen3 Coder 480B A35B (free) can replace Qwen3 VL 235B A22B Instruct when lower sample workload cost matters most: $0.
  • Qwen2.5 7B Instruct can replace Qwen3 VL 235B A22B Instruct when lower sample workload cost matters most: $0.09.
  • Qwen3.5-9B can replace Qwen3 VL 235B A22B Instruct when lower sample workload cost matters most: $0.11.
Larger context near this budget

Cheaper alternatives

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Larger context alternatives

Find models with larger context windows for RAG, long documents, and codebase review.

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Provider catalogs

Compare models within provider hubs before choosing a final API vendor.

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Poolside catalog

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

Open Poolside models

Qwen catalog

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

Open Qwen models
Laguna XS.2 (free)

Laguna XS.2 is the second-generation model in the XS size class from [Poolside](https://poolside.ai), their efficient coding agent series. It combines tool calling and reasoning capabilities with a compact footprint, offering...

Qwen3 VL 235B A22B Instruct

Qwen3-VL-235B-A22B Instruct is an open-weight multimodal model that unifies strong text generation with visual understanding across images and video. The Instruct model targets general vision-language use (VQA, document parsing, chart/table...