API cost decision in 10 seconds

NewQwen3.8 Omni Flash vs Ling 3.0 Flash VL (free)

Pick Ling 3.0 Flash VL (free) for lower cost; pick Qwen3.8 Omni Flash only if the larger context window matters more.

Page updated: 2026-09-22T20:07:50Z Data confirmed: 2026-09-22T21:07:53Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Ling 3.0 Flash VL (free) for lower cost; pick Qwen3.8 Omni Flash only if the larger context window matters more.

On the standard 1M input plus 500K output workload, Ling 3.0 Flash VL (free) is estimated at $0 vs $0.39 for Qwen3.8 Omni Flash, saving $0.39 (100% lower).

Cost-first pickLing 3.0 Flash VL (free)

Context-first pickQwen3.8 Omni Flash

Sample savings$0.39100%

10x traffic gap$3.85

Qwen3.8 Omni Flash has more context, but Ling 3.0 Flash VL (free) saves $0.39 on the standard workload. At 10x that traffic, the same price gap is about $3.85. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Ling 3.0 Flash VL (free) stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	Qwen3.8 Omni Flash	Ling 3.0 Flash VL (free)
Input-heavy / RAG	5M input + 500K output	Ling 3.0 Flash VL (free)	$0.98	$0
Balanced workload	1M input + 1M output	Ling 3.0 Flash VL (free)	$0.62	$0
Output-heavy chatbot	1M input + 5M output	Ling 3.0 Flash VL (free)	$2.5	$0

Cheaper input Ling 3.0 Flash VL (free) $0.15 vs $0 / 1M

Ling 3.0 Flash VL (free) is free for input tokens while Qwen3.8 Omni Flash costs $0.15 per 1M tokens.

Cheaper output Ling 3.0 Flash VL (free) $0.47 vs $0 / 1M

Ling 3.0 Flash VL (free) is free for output tokens while Qwen3.8 Omni Flash costs $0.47 per 1M tokens.

Larger context Qwen3.8 Omni Flash 1M vs 262.14K

Qwen3.8 Omni Flash has 737.86K more context (3.81x larger).

Sample workload Ling 3.0 Flash VL (free) $0.39 vs $0

Ling 3.0 Flash VL (free) is free for the standard workload while the other model is estimated at $0.39.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Qwen3.8 Omni Flash Calculating… Estimated API cost

Ling 3.0 Flash VL (free) 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

Ling 3.0 Flash VL (free) has the lower input price; Ling 3.0 Flash VL (free) has the lower output price; Qwen3.8 Omni Flash offers the larger context window. For the 1M input plus 500K output sample, Ling 3.0 Flash VL (free) is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.39 for Qwen3.8 Omni Flash and $0 for Ling 3.0 Flash VL (free).

Best Fit

Choose Qwen3.8 Omni Flash when you care most about larger context window.

Choose Ling 3.0 Flash VL (free) 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, Ling 3.0 Flash VL (free) is estimated at $0 vs $0.39 for Qwen3.8 Omni Flash, saving $0.39 (100% lower).
Ling 3.0 Flash VL (free) is free for the standard workload while the other model is estimated at $0.39.
Ling 3.0 Flash VL (free) is free for input tokens while Qwen3.8 Omni Flash costs $0.15 per 1M tokens.
Ling 3.0 Flash VL (free) is free for output tokens while Qwen3.8 Omni Flash costs $0.47 per 1M tokens.
Qwen3.8 Omni Flash has 737.86K more context (3.81x larger).

Head-to-Head Specs

Feature	NewQwen3.8 Omni Flash (Qwen)	Ling 3.0 Flash VL (free) (inclusionAI)
Input Price prompt tokens per 1M	$0.15	$0
Completion Price per 1M tokens	$0.47	$0
Sample Workload Cost 1M input + 500K output	$0.39	$0
Context Window	1M	262.14K
Release Date	2026-09-21	2026-09-10

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Ling 3.0 Flash VL (free)	On the standard 1M input plus 500K output workload, Ling 3.0 Flash VL (free) is estimated at $0 vs $0.39 for Qwen3.8 Omni Flash, saving $0.39 (100% lower).
High-volume input processing	Ling 3.0 Flash VL (free)	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Ling 3.0 Flash VL (free)	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Qwen3.8 Omni Flash	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

Qwen3.8 27B (free) can replace Qwen3.8 Omni Flash when lower sample workload cost matters most: $0.
Qwen3 Next 80B A3B Instruct (free) can replace Qwen3.8 Omni Flash when lower sample workload cost matters most: $0.
Qwen3 Coder 480B A35B (free) can replace Qwen3.8 Omni Flash when lower sample workload cost matters most: $0.
Qwen3.7 Flash can replace Qwen3.8 Omni Flash when lower sample workload cost matters most: $0.1.

Larger context near this budget

GLM 5.3 Flash offers 1.31M context with $0.4 sample workload cost.
DeepSeek V4 Flash 0731 offers 1.31M context with $0.36 sample workload cost.
GLM Flash Latest offers 1.31M context with $0.2 sample workload cost.
DeepSeek V4 Flash Latest offers 1.31M context with $0.43 sample workload cost.

Popular competitors

MiMo-V2.6-Pro · Xiaomi · #1
Qwen3.8 Max (0902) · Qwen · #2
DeepSeek V4.1 Flash · DeepSeek · #3
GLM 5.3 Flash · Z.ai · #4

Cheaper alternatives

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Larger context alternatives

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Provider catalogs

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Qwen catalog

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inclusionAI catalog

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Open inclusionAI models

Qwen3.8 Omni Flash

Qwen3.8 Omni Flash is an omni-modal reasoning model from Alibaba, the first Qwen model built around agentic capabilities with native audio-video understanding. It is suited for audio-video analysis and summarization,...

Ling 3.0 Flash VL (free)

Ling 3.0 Flash VL builds on Ling 3.0 Flash (124B total / 5.5B active MoE from InclusionAI), further strengthening its language capabilities while adding native visual perception and advanced visual...