API cost decision in 10 seconds

GPT-5 Nano vs Qwen3 8B

The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.

Page updated: 2026-05-26T15:08:08Z Data confirmed: 2026-05-26T20:08:05Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.

Both models are estimated at $0.25 for the standard 1M input plus 500K output workload.

Cost-first pickTie

Context-first pickGPT-5 Nano

Sample savings$00%

10x traffic gap$0

Context-window winner: GPT-5 Nano. Cost does not separate this pair on the standard workload, so the next decision point is context window and model behavior.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

The two models stay tied across the input-heavy, balanced, and output-heavy sample workloads.

Workload shape	Token mix	Better pick	GPT-5 Nano	Qwen3 8B
Input-heavy / RAG	5M input + 500K output	Tie	$0.45	$0.45
Balanced workload	1M input + 1M output	Tie	$0.45	$0.45
Output-heavy chatbot	1M input + 5M output	Tie	$2.05	$2.05

Cheaper input Tie $0.05 vs $0.05 / 1M

Both models report the same input price at $0.05 per 1M tokens.

Cheaper output Tie $0.4 vs $0.4 / 1M

Both models report the same output price at $0.4 per 1M tokens.

Larger context GPT-5 Nano 400K vs 131.07K

GPT-5 Nano has 268.93K more context (3.05x larger).

Sample workload Tie $0.25 vs $0.25

Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.25.

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

GPT-5 Nano Calculating… Estimated API cost

Qwen3 8B 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

both models tie on input price; both models tie on output price; GPT-5 Nano offers the larger context window. For the 1M input plus 500K output sample, the standard workload cost is tied.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.25 for GPT-5 Nano and $0.25 for Qwen3 8B.

Best Fit

Choose GPT-5 Nano when you care most about larger context window.

Choose Qwen3 8B when its provider, model quality, latency, or availability is more important than the numeric price/context winner.

Decision Notes

Both models are estimated at $0.25 for the standard 1M input plus 500K output workload.
Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.25.
Both models report the same input price at $0.05 per 1M tokens.
Both models report the same output price at $0.4 per 1M tokens.
GPT-5 Nano has 268.93K more context (3.05x larger).

Head-to-Head Specs

Feature	GPT-5 Nano (OpenAI)	Qwen3 8B (Qwen)
Input Price prompt tokens per 1M	$0.05	$0.05
Completion Price per 1M tokens	$0.4	$0.4
Sample Workload Cost 1M input + 500K output	$0.25	$0.25
Context Window	400K	131.07K
Release Date	2025-08-07	2025-04-28
Popularity	#68	#102

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Tie	Both models are estimated at $0.25 for the standard 1M input plus 500K output workload.
High-volume input processing	Tie	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Tie	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	GPT-5 Nano	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

gpt-oss-120b (free) can replace GPT-5 Nano when lower sample workload cost matters most: $0.
gpt-oss-20b (free) can replace GPT-5 Nano when lower sample workload cost matters most: $0.
gpt-oss-20b can replace GPT-5 Nano when lower sample workload cost matters most: $0.1.
gpt-oss-120b can replace GPT-5 Nano when lower sample workload cost matters most: $0.13.

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

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.

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OpenAI catalog

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

Open OpenAI models

Qwen catalog

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

Open Qwen models

GPT-5 Nano

GPT-5-Nano is the smallest and fastest variant in the GPT-5 system, optimized for developer tools, rapid interactions, and ultra-low latency environments. While limited in reasoning depth compared to its larger...

Qwen3 8B

Qwen3-8B is a dense 8.2B parameter causal language model from the Qwen3 series, designed for both reasoning-heavy tasks and efficient dialogue. It supports seamless switching between "thinking" mode for math,...