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Nemotron 3 Ultra vs Qwen3.7 Max

Nemotron 3 Ultra

NVIDIA

40#183
vs
Qwen3.7 Max

Alibaba

40#185
Signal-by-Signal Comparison
SignalNemotron 3 UltraDeltaQwen3.7 Max
Capabilities
67
--
67
Pricing
98
+2
96
Context window size
86
--
86
Recency
100
--
100
Output Capacity
70
-10
80
Overall Result
1 wins
of 5
1 wins
It's a tie - both models win 1 signals each

Score History

Score History (8 data points)
Nemotron 3 UltraQwen3.7 Max
Nemotron 3 Ultra

40

current score

Leader

Tied

right now

Qwen3.7 Max

40

current score

LMMarketCap.com
Interactive Price Comparison
100Kcalls/month
1,000tokens (~1,333 chars)
500tokens (~667 chars)

Nemotron 3 Ultra

NVIDIA

Best Value
Per request$0.001600
Daily$5.33
Monthly$160.00
Annual$1920.00

Qwen3.7 Max

Alibaba

Per request$0.003125
Daily$10.42
Monthly$312.50
Annual$3750.00

Nemotron 3 Ultra saves you $152.50/month

That's $1830.00/year compared to Qwen3.7 Max at your current usage level of 100K calls/month.

49% cheaper
Choose Nemotron 3 Ultra for cost optimization

Nemotron 3 Ultra pricing:
Input:$0.50/M tokens
Output:$2.20/M tokens
Qwen3.7 Max pricing:
Input:$1.25/M tokens
Output:$3.75/M tokens
Tie
Nemotron 3 Ultra

NVIDIA

40

Composite Score

Tie
Qwen3.7 Max

Alibaba

40

Composite Score

Signal-by-Signal Comparison
MetricNemotron 3 UltraQwen3.7 MaxWinner
Overall Score
40
40
--
Rank#183#185
Nemotron 3 Ultra
Quality Rank#183#185
Nemotron 3 Ultra
Adoption Rank#183#185
Nemotron 3 Ultra
Parameters550B----
Context Window1000K1000K--
Pricing$0.50/$2.20/M$1.25/$3.75/M--
Signal Scores
Capabilities
67
67
Nemotron 3 Ultra
Pricing
98
96
Nemotron 3 Ultra
Context window size
86
86
Nemotron 3 Ultra
Recency
100
100
Nemotron 3 Ultra
Output Capacity
70
80
Qwen3.7 Max
Benchmark Interpretation

Our score (0-100) is driven by benchmark performance (90%) from Arena Elo ratings, MMLU, GPQA, HumanEval, SWE-bench, and 15+ standardized evaluations. Capabilities and context window serve as tiebreakers (10%). Learn more about our methodology.

Nemotron 3 UltraEntry Level

Scores 40/100 (rank #183), placing it in the top 37% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100
Qwen3.7 MaxEntry Level

Scores 40/100 (rank #185), placing it in the top 37% of all 290 models tracked.

Raw Quality0/100
Cost Efficiency0/100
Speed0/100

With only a 0-point gap, these models are in the same performance tier. The practical difference in output quality is minimal - your choice should depend on pricing, latency requirements, and specific feature needs.

When to Use Each Model

Choose Nemotron 3 Ultra when you need:

  • High-volume production workloads where API costs must be minimized
  • Step-by-step reasoning and chain-of-thought problem solving
  • Self-hosted deployments where you need full control over the model

Choose Qwen3.7 Max when you need:

  • Step-by-step reasoning and chain-of-thought problem solving
Cost-Performance Analysis
Nemotron 3 UltraBest Value
Input cost$0.50/M tokens
Output cost$2.20/M tokens
Cost per quality point$0.068
Est. monthly (1M tokens/day)$40.50
Qwen3.7 Max
Input cost$1.25/M tokens
Output cost$3.75/M tokens
Cost per quality point$0.125
Est. monthly (1M tokens/day)$75.00

Nemotron 3 Ultra offers 46% better value per quality point. At 1M tokens/day, you'd spend $40.50/month with Nemotron 3 Ultra vs $75.00/month with Qwen3.7 Max - a $34.50 monthly difference.

Latency & Speed
Nemotron 3 UltraFaster
Speed score0/100
Qwen3.7 Max
Speed score0/100

Both models have comparable response speeds. For most applications, the latency difference is negligible.

When latency matters most: Interactive chatbots, IDE code completion, real-time translation, and user-facing applications where response time directly impacts experience. For batch processing, background summarization, or offline analysis, latency is less critical.

Example Use Cases

Code generation & review

Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring

Nemotron 3 Ultra

Customer support chatbot

Suitable for user-facing chat with competitive response times. Nemotron 3 Ultra also offers lower per-token costs for high-volume support

Nemotron 3 Ultra

Long document analysis

Larger context window (1000K tokens) can process longer documents, contracts, and research papers in a single pass

Nemotron 3 Ultra

Batch data extraction

Lower output pricing ($2.20/M) reduces costs when processing thousands of records daily

Nemotron 3 Ultra

Creative writing & content

Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content

Nemotron 3 Ultra
Which Should You Choose?
Our recommendation:
Nemotron 3 Ultra

Nemotron 3 Ultra and Qwen3.7 Max are extremely close in overall performance (only 0 points apart). Your best choice depends entirely on which specific strengths matter most for your use case.

Nemotron 3 Ultra
Recommended

by NVIDIA

  • Choose for Quality - Marginally better benchmark scores; both are excellent
  • Choose for Cost - 46% lower pricing; better value at scale
  • Choose for Reliability - Higher uptime and faster response speeds
  • Choose for Prototyping - Stronger community support and better developer experience
  • Choose for Production - Wider enterprise adoption and proven at scale

by Alibaba

Consider for specialized use cases.

Capability Comparison
CapabilityNemotron 3 UltraQwen3.7 Max
Vision (Image Input)
Function Calling
Streaming
JSON Mode
Reasoning
Web Search
Image Output
Monthly Cost Calculator
1,000tokens (600 in / 400 out)
100requests/day (3,000/month)

Nemotron 3 Ultra

NVIDIA

Best Value
$3.54
estimated monthly cost

Qwen3.7 Max

Alibaba

$6.75
estimated monthly cost

Nemotron 3 Ultra saves you $3.21/month

That's 48% cheaper than Qwen3.7 Max at 1,000 tokens/request and 100 requests/day.

Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.

Parameters & Context
ParameterNemotron 3 UltraQwen3.7 Max
Context Window1M1M
Max Output Tokens16,38465,536
Open SourceYesNo
CreatedJun 4, 2026May 21, 2026
Last updated: 47m ago

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