API cost decision in 10 seconds

🔥Nemotron 3.5 Content Safety vs 🔥Hunyuan A13B Instruct

Pick Nemotron 3.5 Content Safety when budget is the priority.

Page updated: 2026-09-04T00:14:07Z Data confirmed: 2026-09-08T23:08:16Z Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick Nemotron 3.5 Content Safety when budget is the priority.

On the standard 1M input plus 500K output workload, Nemotron 3.5 Content Safety is estimated at $0.3 vs $0.42 for Hunyuan A13B Instruct, saving $0.12 (29.4% lower).

Cost-first pickNemotron 3.5 Content Safety

Context-first pickBoth models

Sample savings$0.1229.4%

10x traffic gap$1.25

The reported context window is tied, so cost and provider fit carry more weight. At 10x that traffic, the same price gap is about $1.25. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

Cost winner changes by workload shape: input-heavy / RAG favors Hunyuan A13B Instruct, balanced workload favors Nemotron 3.5 Content Safety, and output-heavy chatbot favors Nemotron 3.5 Content Safety.

Workload shape	Token mix	Better pick	Nemotron 3.5 Content Safety	Hunyuan A13B Instruct
Input-heavy / RAG	5M input + 500K output	Hunyuan A13B Instruct	$1.1	$0.99
Balanced workload	1M input + 1M output	Nemotron 3.5 Content Safety	$0.4	$0.71
Output-heavy chatbot	1M input + 5M output	Nemotron 3.5 Content Safety	$1.2	$2.99

Cheaper input Hunyuan A13B Instruct $0.2 vs $0.14 / 1M

Hunyuan A13B Instruct is $0.06 cheaper per 1M input tokens (30% lower; 1.43x difference).

Cheaper output Nemotron 3.5 Content Safety $0.2 vs $0.57 / 1M

Nemotron 3.5 Content Safety is $0.37 cheaper per 1M output tokens (64.9% lower; 2.85x difference).

Larger context Tie 131.07K vs 131.07K

Both models report the same context window at 131.07K tokens.

Sample workload Nemotron 3.5 Content Safety $0.3 vs $0.42

Nemotron 3.5 Content Safety is $0.12 cheaper on the standard workload (29.4% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.

Monthly input tokens Monthly output tokens

Nemotron 3.5 Content Safety Calculating… Estimated API cost

Hunyuan A13B 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

Hunyuan A13B Instruct has the lower input price; Nemotron 3.5 Content Safety has the lower output price; both models report the same context window. For the 1M input plus 500K output sample, Nemotron 3.5 Content Safety is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.3 for Nemotron 3.5 Content Safety and $0.42 for Hunyuan A13B Instruct.

Best Fit

Choose Nemotron 3.5 Content Safety when you care most about lower output-token price.

Choose Hunyuan A13B Instruct when you care most about lower input-token price.

Decision Notes

On the standard 1M input plus 500K output workload, Nemotron 3.5 Content Safety is estimated at $0.3 vs $0.42 for Hunyuan A13B Instruct, saving $0.12 (29.4% lower).
Nemotron 3.5 Content Safety is $0.12 cheaper on the standard workload (29.4% lower).
Hunyuan A13B Instruct is $0.06 cheaper per 1M input tokens (30% lower; 1.43x difference).
Nemotron 3.5 Content Safety is $0.37 cheaper per 1M output tokens (64.9% lower; 2.85x difference).
Both models report the same context window at 131.07K tokens.

Head-to-Head Specs

Feature	🔥Nemotron 3.5 Content Safety (NVIDIA)	🔥Hunyuan A13B Instruct (Tencent)
Input Price prompt tokens per 1M	$0.2	$0.14
Completion Price per 1M tokens	$0.2	$0.57
Sample Workload Cost 1M input + 500K output	$0.3	$0.42
Context Window	131.07K	131.07K
Release Date	2026-06-04	2025-07-08
Popularity	#15	#18

Use-Case Decision Matrix

Use case	Better pick	Why
Budget-constrained production	Nemotron 3.5 Content Safety	On the standard 1M input plus 500K output workload, Nemotron 3.5 Content Safety is estimated at $0.3 vs $0.42 for Hunyuan A13B Instruct, saving $0.12 (29.4% lower).
High-volume input processing	Hunyuan A13B Instruct	Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbots	Nemotron 3.5 Content Safety	Lower output-token price matters most when assistants generate many completion tokens.
RAG or long-document work	Tie	A larger context window leaves more room for retrieved passages, conversation history, or source files.

Related Alternatives

Same-provider lower-cost swaps

Nemotron 3 Ultra (free) can replace Nemotron 3.5 Content Safety when lower sample workload cost matters most: $0.
Nemotron 3.5 Lightning (free) can replace Nemotron 3.5 Content Safety when lower sample workload cost matters most: $0.
Nemotron 3.5 Content Safety (free) can replace Nemotron 3.5 Content Safety when lower sample workload cost matters most: $0.
Nemotron 3 Nano Omni (free) can replace Nemotron 3.5 Content Safety when lower sample workload cost matters most: $0.

Larger context near this budget

DeepSeek V4 Flash 0731 offers 1.31M context with $0.15 sample workload cost.
GLM 5.3 Flash offers 1.31M context with $0.2 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 $0.13 sample workload cost.

Popular competitors

Hy4 preview · Tencent · #1
GPT-5.6 Luna · OpenAI · #2
DeepSeek V4 Flash 0731 · DeepSeek · #3
GLM 5.3 Flash · Z.ai · #4

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

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NVIDIA catalog

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

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Tencent catalog

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

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Nemotron 3.5 Content Safety

NVIDIA Nemotron 3.5 Content Safety is a compact 4B-parameter multimodal guardrail model from NVIDIA, fine-tuned from Google Gemma-3-4B. It moderates both inputs to and responses from LLMs and VLMs, accepting...

Hunyuan A13B Instruct

Hunyuan-A13B is a 13B active parameter Mixture-of-Experts (MoE) language model developed by Tencent, with a total parameter count of 80B and support for reasoning via Chain-of-Thought. It offers competitive benchmark...