API cost decision in 10 seconds

Qwen3 VL 235B A22B Instruct vs gpt-oss-safeguard-20b

Pick gpt-oss-safeguard-20b for lower cost; pick Qwen3 VL 235B A22B Instruct only if the larger context window matters more.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T19:08:13Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick gpt-oss-safeguard-20b 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, gpt-oss-safeguard-20b is estimated at $0.22 vs $0.64 for Qwen3 VL 235B A22B Instruct, saving $0.42 (64.8% lower).

Cost-first pickgpt-oss-safeguard-20b

Context-first pickQwen3 VL 235B A22B Instruct

Sample savings$0.4264.8%

10x traffic gap$4.15

Qwen3 VL 235B A22B Instruct has more context, but gpt-oss-safeguard-20b saves $0.42 on the standard workload. At 10x that traffic, the same price gap is about $4.15. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

gpt-oss-safeguard-20b stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Qwen3 VL 235B A22B Instruct	gpt-oss-safeguard-20b
Input-heavy / RAG	5M input + 500K output	gpt-oss-safeguard-20b	$1.44	$0.53
Balanced workload	1M input + 1M output	gpt-oss-safeguard-20b	$1.08	$0.38
Output-heavy chatbot	1M input + 5M output	gpt-oss-safeguard-20b	$4.6	$1.57

Cheaper input gpt-oss-safeguard-20b $0.2 vs $0.075 / 1M

gpt-oss-safeguard-20b is $0.12 cheaper per 1M input tokens (62.5% lower; 2.67x difference).

Cheaper output gpt-oss-safeguard-20b $0.88 vs $0.3 / 1M

gpt-oss-safeguard-20b is $0.58 cheaper per 1M output tokens (65.9% lower; 2.93x difference).

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

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

Sample workload gpt-oss-safeguard-20b $0.64 vs $0.22

gpt-oss-safeguard-20b is $0.42 cheaper on the standard workload (64.8% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Qwen3 VL 235B A22B Instruct Calculating… Estimated API cost

gpt-oss-safeguard-20b 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

gpt-oss-safeguard-20b has the lower input price; gpt-oss-safeguard-20b has the lower output price; Qwen3 VL 235B A22B Instruct offers the larger context window. For the 1M input plus 500K output sample, gpt-oss-safeguard-20b is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.64 for Qwen3 VL 235B A22B Instruct and $0.22 for gpt-oss-safeguard-20b.

Best Fit

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

Choose gpt-oss-safeguard-20b 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, gpt-oss-safeguard-20b is estimated at $0.22 vs $0.64 for Qwen3 VL 235B A22B Instruct, saving $0.42 (64.8% lower).
gpt-oss-safeguard-20b is $0.42 cheaper on the standard workload (64.8% lower).
gpt-oss-safeguard-20b is $0.12 cheaper per 1M input tokens (62.5% lower; 2.67x difference).
gpt-oss-safeguard-20b is $0.58 cheaper per 1M output tokens (65.9% lower; 2.93x difference).
Qwen3 VL 235B A22B Instruct has 131.07K more context (2x larger).

Head-to-Head Specs

Feature	Qwen3 VL 235B A22B Instruct (Qwen)	gpt-oss-safeguard-20b (OpenAI)
Input Price prompt tokens per 1M	$0.2	$0.075
Completion Price per 1M tokens	$0.88	$0.3
Sample Workload Cost 1M input + 500K output	$0.64	$0.22
Context Window	262.14K	131.07K
Release Date	2025-09-23	2025-10-29
Popularity	#103	#124

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	gpt-oss-safeguard-20b	On the standard 1M input plus 500K output workload, gpt-oss-safeguard-20b is estimated at $0.22 vs $0.64 for Qwen3 VL 235B A22B Instruct, saving $0.42 (64.8% lower).
High-volume input processing	gpt-oss-safeguard-20b	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	gpt-oss-safeguard-20b	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Qwen3 VL 235B A22B Instruct	A 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

Llama 4 Scout offers 10M context with $0.23 sample workload cost.
Owl Alpha offers 1.05M context with $0 sample workload cost.
DeepSeek V4 Flash offers 1.05M context with $0.2 sample workload cost.
Gemini 2.5 Flash Lite offers 1.05M context with $0.3 sample workload cost.

Popular competitors

DeepSeek V4 Flash · DeepSeek · #1
Hy3 preview · Tencent · #2
Claude Opus 4.7 · Anthropic · #3
Claude Sonnet 4.6 · Anthropic · #4

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Larger context alternatives

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Provider catalogs

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Qwen catalog

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OpenAI catalog

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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...

gpt-oss-safeguard-20b

gpt-oss-safeguard-20b is a safety reasoning model from OpenAI built upon gpt-oss-20b. This open-weight, 21B-parameter Mixture-of-Experts (MoE) model offers lower latency for safety tasks like content classification, LLM filtering, and trust...