Both models report the same input price at $0.25 per 1M tokens.
API cost decision in 10 seconds
NewParticle-1 vs NewBeam 1.0 501B A23B
The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.
Page updated:
Data confirmed:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
The standard workload cost is tied; choose by context window, provider fit, latency, or model quality.
Both models are estimated at $0.75 for the standard 1M input plus 500K output workload.
Cost-first pickTie
Context-first pickBoth models
Sample savings$00%
10x traffic gap$0
Context-window winner: Both models. Cost does not separate this pair on the standard workload, so the next decision point is context window and model behavior.
Cost sensitivity
Workload Sensitivity
The two models stay tied across the input-heavy, balanced, and output-heavy sample workloads.
| Workload shape | Token mix | Better pick | Particle-1 | Beam 1.0 501B A23B |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | Tie | $1.75 | $1.75 |
| Balanced workload | 1M input + 1M output | Tie | $1.25 | $1.25 |
| Output-heavy chatbot | 1M input + 5M output | Tie | $5.25 | $5.25 |
Both models report the same output price at $1 per 1M tokens.
Both models report the same context window at 1.05M tokens.
Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.75.
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
both models tie on input price; both models tie on output price; both models report the same context window. For the 1M input plus 500K output sample, the standard workload cost is tied.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.75 for Particle-1 and $0.75 for Beam 1.0 501B A23B.
Choose Particle-1 when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
Choose Beam 1.0 501B A23B when its provider, model quality, latency, or availability is more important than the numeric price/context winner.
- Both models are estimated at $0.75 for the standard 1M input plus 500K output workload.
- Both models have the same estimated cost for the standard 1M input plus 500K output workload: $0.75.
- Both models report the same input price at $0.25 per 1M tokens.
- Both models report the same output price at $1 per 1M tokens.
- Both models report the same context window at 1.05M tokens.
| Feature | NewParticle-1 (Particle AI) | NewBeam 1.0 501B A23B (Reflection) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.25 | $0.25 |
| Completion Price per 1M tokens | $1 | $1 |
| Sample Workload Cost 1M input + 500K output | $0.75 | $0.75 |
| Context Window | 1.05M | 1.05M |
| Release Date |
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | Tie | Both models are estimated at $0.75 for the standard 1M input plus 500K output workload. |
| High-volume input processing | Tie | Lower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill. |
| Long responses and chatbots | Tie | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | Tie | A larger context window leaves more room for retrieved passages, conversation history, or source files. |
Related Alternatives
- No lower-cost same-provider swap is currently tracked for this pair.
- Llama 4 Scout offers 1.31M context with $0.25 sample workload cost.
- GPT-6 Luna offers 1.05M context with $0.35 sample workload cost.
- MiMo-V2.6-Flash offers 1.05M context with $0.28 sample workload cost.
- GPT-6 Luna Pro offers 1.05M context with $0.35 sample workload cost.
- Kimi K3.1 Pro · MoonshotAI · #1
- DeepSeek V4.1 Flash 1017 · DeepSeek · #2
- DeepSeek V4.1 Flash · DeepSeek · #3
- GLM 5.3 Flash · Z.ai · #4
Cheaper alternatives
Review low-cost models sorted by a standard 1M input plus 500K output workload.
Open cheapest modelsLarger context alternatives
Find models with larger context windows for RAG, long documents, and codebase review.
Open largest context modelsProvider catalogs
Compare models within provider hubs before choosing a final API vendor.
Open provider hubsParticle AI catalog
Review all tracked Particle AI models before deciding whether this matchup is the right shortlist.
Open Particle AI modelsReflection catalog
Check other Reflection models with comparable pricing, context, or release timing.
Open Reflection modelsParticle-1 is a token-efficient agentic coding model from Particle AI, post-trained on DeepSeek V4.1 Flash. It is suited for software engineering work such as terminal workflows, codebase changes, and data...
Beam 1.0 is Reflection's open-weight reasoning model for coding and long-horizon agentic workflows. It uses a sparse mixture-of-experts architecture with 501B total and 23B active parameters per token, and a...