ALLaM 34B vs Nemotron Nano 9B V2 (free)
| Signal | ALLaM 34B | Delta | Nemotron Nano 9B V2 (free) |
|---|---|---|---|
Capabilities | 17 | -50 | |
Pricing | 100 | -- | |
Context window size | 57 | -24 | |
Recency | 69 | -2 | |
Output Capacity | 60 | +40 | |
| Overall Result | 1 wins | of 5 | 3 wins |
Score History
40
current score
Tied
right now
40
current score
ALLaM 34B
HUMAIN
Nemotron Nano 9B V2 (free)
NVIDIA
| Metric | ALLaM 34B | Nemotron Nano 9B V2 (free) | Winner |
|---|---|---|---|
| Overall Score | 40 | 40 | -- |
| Rank | #321 | #320 | Nemotron Nano 9B V2 (free) |
| Quality Rank | #321 | #320 | Nemotron Nano 9B V2 (free) |
| Adoption Rank | #321 | #320 | Nemotron Nano 9B V2 (free) |
| Parameters | 34B | 9B | -- |
| Context Window | 4K | 128K | Nemotron Nano 9B V2 (free) |
| Pricing | Free | Free | -- |
| Signal Scores | |||
| Capabilities | 17 | 67 | Nemotron Nano 9B V2 (free) |
| Pricing | 100 | 100 | ALLaM 34B |
| Context window size | 57 | 81 | Nemotron Nano 9B V2 (free) |
| Recency | 69 | 72 | Nemotron Nano 9B V2 (free) |
| Output Capacity | 60 | 20 | ALLaM 34B |
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.
Scores 40/100 (rank #321), placing it in the top -10% of all 290 models tracked.
Scores 40/100 (rank #320), placing it in the top -10% of all 290 models tracked.
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.
Choose ALLaM 34B when you need:
- Budget-friendly applications with moderate quality requirements
Choose Nemotron Nano 9B V2 (free) when you need:
- Processing long documents or large codebases (128K token context)
- Agentic applications using tool/function calling
- Step-by-step reasoning and chain-of-thought problem solving
- Self-hosted deployments where you need full control over the model
Both models are priced similarly, so the decision comes down to quality and features rather than cost.
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.
Code generation & review
Based on overall model capabilities and architecture for coding tasks like generating functions, debugging, and refactoring
Customer support chatbot
Suitable for user-facing chat with competitive response times. ALLaM 34B also offers lower per-token costs for high-volume support
Long document analysis
Larger context window (128K tokens) can process longer documents, contracts, and research papers in a single pass
Batch data extraction
Lower output pricing ($0.00/M) reduces costs when processing thousands of records daily
Creative writing & content
Higher overall composite score (40/100) correlates with better nuance, coherence, and style in long-form content
ALLaM 34B and Nemotron Nano 9B V2 (free) 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.
By Use Case
Best for Quality
ALLaM 34B
Marginally better benchmark scores; both are excellent
Best for Cost
ALLaM 34B
0% lower pricing; better value at scale
Best for Reliability
ALLaM 34B
Higher uptime and faster response speeds
Best for Prototyping
ALLaM 34B
Stronger community support and better developer experience
Best for Production
ALLaM 34B
Wider enterprise adoption and proven at scale
by HUMAIN
- Choose for Quality - Marginally better benchmark scores; both are excellent
- Choose for Cost - 0% 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
| Capability | ALLaM 34B | Nemotron Nano 9B V2 (free) |
|---|---|---|
| Vision (Image Input) | ||
| Function Callingdiffers | ||
| Streaming | ||
| JSON Modediffers | ||
| Reasoningdiffers | ||
| Web Search | ||
| Image Output |
ALLaM 34B
HUMAIN
Nemotron Nano 9B V2 (free)
NVIDIA
Assumes 60% input / 40% output token ratio per request. Actual costs may vary based on your usage pattern.
| Parameter | ALLaM 34B | Nemotron Nano 9B V2 (free) |
|---|---|---|
| Context Window | 4K | 128K |
| Max Output Tokens | 4,096 | -- |
| Open Source | No | Yes |
| Created | Aug 25, 2025 | Sep 5, 2025 |