Models

Nvidia Nemotron 3 Super 120B A12B vs Qwen3.8 Max Preview

Compare Nvidia Nemotron 3 Super 120B A12B from Nvidia and Qwen3.8 Max Preview from Qwen on key metrics including benchmarks, price, context length, and other model features. Access both models and hundreds of others through the AIHubMix API.

NvidiaNvidia Nemotron 3 Super 120B A12BQwenQwen3.8 Max Preview
Nvidia logo
Nvidia Nemotron 3 Super 120B A12B
Nvidia · text → text

An open-source, efficient hybrid Mamba-Transformer MoE model that supports a context length of one million tokens and excels at agent reasoning, programming, planning, and tool invocation.

Input$0.11 /M
Output$0.55 /M
Qwen logo
Qwen3.8 Max Preview
Qwen · text, image → text

Qwen 3.8 Max Preview(Qwen3.8-Max-Preview) is the latest-generation foundation model in the Qwen family, packing 2.4T parameters and still evolving. Compared with the previous flagship Qwen 3.7 Max, it delivers major gains in core capabilities like Coding and Cowork (professional productivity), with world-leading performance on complex, long-horizon tasks such as full-stack development, data analysis, and Office workflows. Launch offer: Credits are consumed at just 20% of the standard rate, effectively 5× your usage. Limited time only.

Input$0.34 /M
Output$1.01 /M

Pricing & Specifications

Prices are per million tokens. Time to First Token and throughput are rolling averages measured on AIHubMix.

Nvidia Nemotron 3 Super 120B A12B
Qwen3.8 Max Preview
Input /M
$0.11
$0.34
Output /M
$0.55
$1.01
Cache read /M
$0.03
$0.03
Context length
1,000,000
983,616
Max output
0
131,072
Time to First Token
-
2.4 s
Throughput
-
48.1 tok/s
Modalities
text
textimage
Supported Parameters
thinkingtoolsfunction callingstructured outputslong context
toolsfunction callingstructured outputsweblong contextthinking
API Formats
Released
-
-

Promotional prices show the discounted rate; see each model page for promotion windows.

Activity Past 30 Days

Daily traffic served through AIHubMix — how demand for each model is trending.

nvidia-nemotron-3-super-120b-a12bqwen3.8-max-preview

Tokens / day

-

Requests / day

-

Performance Past 3 Days

Measured on real AIHubMix traffic, hourly buckets. Gaps mean no traffic in that hour.

nvidia-nemotron-3-super-120b-a12bqwen3.8-max-preview

Throughput (tok/s)

-

TTFT (s)

-

Uptime (%)

-

LMArena Benchmarks

LMArena ratings by capability (Bradley-Terry, commonly called Elo). Higher is better.

Text
nvidia-nemotron-3-super-120b-a12bqwen3.8-max-preview
1280136014401520
Overall
13621481
Coding
14111520
Math
13761504
Hard prompts
13811506
Instruction following
13461478
Multi-turn
13501496
Creative writing
13041469
Longer query
13611497
Chinese
14031545
English
13851486

Source: LMArena (arena.ai) leaderboard, imported by AIHubMix. Models without published ratings are omitted per chart.

Cost calculator

Estimate your monthly bill for the same workload on each model.

Nvidia Nemotron 3 Super 120B A12B
$14.85 /mo
Qwen3.8 Max Preview
$35.49 /mo

Monthly = daily × 30. Discounted rates applied where a promotion is active.

FAQ

Which is cheaper: Nvidia Nemotron 3 Super 120B A12B, Qwen3.8 Max Preview?

Nvidia Nemotron 3 Super 120B A12B: $0.55/M output tokens; Qwen3.8 Max Preview: $1.01/M. Use the cost calculator above to estimate your own workload.

How do their coding arena scores compare?

Qwen3.8 Max Preview: 1520; Nvidia Nemotron 3 Super 120B A12B: 1411 (LMArena coding leaderboard).

How large is each context window?

Nvidia Nemotron 3 Super 120B A12B accepts 1,000,000 and Qwen3.8 Max Preview accepts 983,616 input tokens.

What inputs and capabilities does each model support?

Nvidia Nemotron 3 Super 120B A12B accepts text input and supports thinking, tool calling, function calling, structured outputs and long context; Qwen3.8 Max Preview accepts text and image input and supports tool calling, function calling, structured outputs, web search, long context and thinking.

Can I call Nvidia Nemotron 3 Super 120B A12B and Qwen3.8 Max Preview with the same API key?

Yes. AIHubMix serves every model on this page behind one OpenAI-compatible endpoint, so switching between them is a one-line change to the model field — no second account, key or SDK.

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