Beam 1.0 vs QwQ-32B-Preview
Beam 1.0 leads the LLM Stats Score 44.6 to 8.5. QwQ-32B-Preview is 3.7x cheaper per token.
Reflection AI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Beam 1.0 leads the overall LLM Stats Score 44.6 to 8.5, ranking #46 overall.
In the 2 individual benchmarks reported for both models, Beam 1.0 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, QwQ-32B-Preview is roughly 3.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Beam 1.0 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Beam 1.0
- overall performance matters — it scores 44.6 and ranks #46 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
Choose QwQ-32B-Preview
- cost matters — it's about 3.7x cheaper per token
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
22 reported for Beam 1.0 · 4 for QwQ-32B-Preview
Beam 1.0 outperforms in 2 benchmarks (GPQA, LiveCodeBench), while QwQ-32B-Preview is better at 0 benchmarks.
Beam 1.0 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Beam 1.0 ($0.40/1M tokens) is 2.7x more expensive than QwQ-32B-Preview ($0.15/1M tokens).
For output processing, Beam 1.0 ($1.20/1M tokens) is 6.0x more expensive than QwQ-32B-Preview ($0.20/1M tokens).
In conclusion, Beam 1.0 is more expensive than QwQ-32B-Preview.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Beam 1.0 has 468.8B more parameters than QwQ-32B-Preview, making it 1442.5% larger.
Context Window
Maximum input and output token capacity
Beam 1.0 accepts 1,048,576 input tokens compared to QwQ-32B-Preview's 32,768 tokens. Beam 1.0 can generate longer responses up to 131,072 tokens, while QwQ-32B-Preview is limited to 32,768 tokens.
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Beam 1.0 was released on 2026-10-16, while QwQ-32B-Preview was released on 2024-11-28.
Beam 1.0 is 23 months newer than QwQ-32B-Preview.
Oct 16, 2026
3 days ago
1.9yr newerNov 28, 2024
1.9 years ago
Knowledge Cutoff
When training data ends
Beam 1.0 has a knowledge cutoff of 2026-06-30, while QwQ-32B-Preview has a cutoff of 2024-11-28.
Beam 1.0 has more recent training data (up to 2026-06-30), making it potentially better informed about events through that date compared to QwQ-32B-Preview (2024-11-28).
Jun 2026
1.6 yr newerNov 2024
Provider Availability
Beam 1.0 is available from Together, Reflection AI. QwQ-32B-Preview is available from DeepInfra, Hyperbolic, Fireworks, Together.
Beam 1.0
QwQ-32B-Preview
Outputs Comparison
Judge for yourself.
Run your own prompts against Beam 1.0 and QwQ-32B-Preview side-by-side, then vote on the output you prefer.
FAQ
Common questions about Beam 1.0 vs QwQ-32B-Preview.