Compare the listed model data for DeepSeek-R1 Distill Qwen 1.5B by DeepSeek and Llama 3.2 1B Instruct by Meta Llama. Benchmark and pricing records are not a controlled test and may change.
Data last updated: 2026-10-16. Verify current model details with each provider.
What the listed data says
DeepSeek-R1 Distill Qwen 1.5B: 32K tokens; Llama 3.2 1B Instruct: 128K tokens. Llama 3.2 1B Instruct has the larger listed context window. DeepSeek-R1 Distill Qwen 1.5B is listed for reasoning; Llama 3.2 1B Instruct is listed for no specific capability flags. Shared catalog benchmark entries: No shared benchmark labels are listed in these model records. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
Catalog source links
Use these model and provider links to verify current specifications, pricing, and availability.
The listed context windows are 32K tokens and 128K tokens; the larger is 4× the smaller.
No shared benchmark labels are present in both catalog records.
The first listed parameter quantities are 1.5B and 1B; the larger quantity is 1.5× the smaller. Total and active MoE parameters are not directly equivalent.
The catalog release dates are January 2025 and September 2024, about 4 months apart at the precision supplied.
Cost example: 1M input and 1M output tokens
A cost example for 1M input plus 1M output tokens cannot be calculated reliably because separate numeric input and output rates are not listed for both models.
Choose DeepSeek-R1 Distill Qwen 1.5B if…
Choose DeepSeek-R1 Distill Qwen 1.5B when your task aligns with catalog-listed uses or strengths such as On-device AI on smartphones and embedded systems, Educational apps demonstrating chain-of-thought reasoning, Offline AI in connectivity-limited environments, Lightest reasoning model ever publicly released at 1.5B.
Choose Llama 3.2 1B Instruct if…
Choose Llama 3.2 1B Instruct when your task aligns with catalog-listed uses or strengths such as On-device AI in mobile apps requiring privacy, IoT AI assistants, Ultra-compact — runs on CPU, mobile, embedded hardware, 128K context at 1B scale.
Catalog specifications for DeepSeek-R1 Distill Qwen 1.5B and Llama 3.2 1B Instruct
Specification
DeepSeek-R1 Distill Qwen 1.5B
Llama 3.2 1B Instruct
Provider
DeepSeek
Meta Llama
Parameters
1.5B
1B
Context window
32K tokens
128K tokens
Maximum output
Not listed
Not listed
Catalog pricing
MIT — free
Free — Llama 3.2 Community License
Listed input/output cost per 1M tokens
Separate numeric input/output rates not listed
Separate numeric input/output rates not listed
License
MIT
Llama 3.2 Community License
Coding support
Not listed
Not listed
Reasoning support
Listed
Not listed
Vision input
Not listed
Not listed
Multimodal
Not listed
Not listed
Open weights
Yes
Yes
Figures are transcribed from LITHOVEX model records. Benchmark versions and evaluation setups may differ; pricing and specifications can change. Check each provider's current documentation before making a decision.
Frequently Asked Questions
What is different between DeepSeek-R1 Distill Qwen 1.5B and Llama 3.2 1B Instruct?
DeepSeek-R1 Distill Qwen 1.5B: 32K tokens; Llama 3.2 1B Instruct: 128K tokens. Llama 3.2 1B Instruct has the larger listed context window. DeepSeek-R1 Distill Qwen 1.5B is listed for reasoning; Llama 3.2 1B Instruct is listed for no specific capability flags. Shared catalog benchmark entries: No shared benchmark labels are listed in these model records. These records are reference data, not a controlled head-to-head test; verify current pricing and specifications with each provider.
What benchmark values are listed for DeepSeek-R1 Distill Qwen 1.5B and Llama 3.2 1B Instruct?
No shared benchmark labels are listed in these model records. The catalog values may use different versions and evaluation setups, so they are reference points rather than a controlled head-to-head result.
What are the listed costs per million tokens for DeepSeek-R1 Distill Qwen 1.5B and Llama 3.2 1B Instruct?
DeepSeek-R1 Distill Qwen 1.5B: Separate numeric input/output rates not listed (MIT — free). Llama 3.2 1B Instruct: Separate numeric input/output rates not listed (Free — Llama 3.2 Community License). Where separate numeric input and output rates are available, the worked example uses 1M input plus 1M output tokens. Confirm current terms with each provider.
How far apart are the listed release dates for DeepSeek-R1 Distill Qwen 1.5B and Llama 3.2 1B Instruct?
The catalog lists DeepSeek-R1 Distill Qwen 1.5B as January 2025 and Llama 3.2 1B Instruct as September 2024, about 4 months apart at the precision supplied.
When was the comparison data last updated?
The model catalog records 2026-10-16 as its data update date. Provider specifications and prices may have changed since then.
How should I choose between DeepSeek-R1 Distill Qwen 1.5B and Llama 3.2 1B Instruct?
Compare the listed specifications and capabilities, review the benchmark notes, then test both with the same representative prompt for your task. This page does not claim a universal winner.
Create your free LITHOVEX account and compare DeepSeek-R1 Distill Qwen 1.5B and Llama 3.2 1B Instruct on your actual tasks. No credit card, no API key, no subscriptions needed.