Claude Sonnet 5 vs Particle-1
Anthropic · US | Particle AI · US · Updated June 2026
Quick verdict
Pick Claude Sonnet 5 for agentic workflows that plan, use tools, and run autonomously or multi-step coding, debugging, and tool use. Pick Particle-1 for token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash or particle reports 72.57% task pass rate versus 71.15% for deepseek v4.1 flash, at $0.2211 versus $0.3368 per task. On a tight budget at scale, Particle-1 is the value pick.
Claude Sonnet 5 (Anthropic) and Particle-1 (Particle AI) are two of the models people most often weigh against each other in 2026. Claude Sonnet 5 is anthropic's most agentic Sonnet, with near-Opus-4.8 performance at Sonnet prices; the default model on Free and Pro. Particle-1 is particle AI's October 28, 2026 debut - a closed, token-efficient coding model post-trained on DeepSeek V4.1 Flash, with 1M context at $0.25/$1.00 at peak rates. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
- ▸Price: Particle-1 is about 8× cheaper on input ($0.25/$1 per 1M tokens vs $2/$10 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: 1M vs 1M tokens — within a few percent of each other, so treat this as a tie and test on your own long inputs, since usable recall varies by model.
- ▸Recency: Particle-1 is the newer model by about 4 months (released October 28, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Claude Sonnet 5 | Particle-1 |
|---|---|---|
| Provider | Anthropic (US) | Particle AI (US) |
| Released | June 30, 2026 | October 28, 2026 |
| Context window | 1M (~1,500 pages) | 1M tokens (~1,573 pages) |
| Price (in/out) | $2/$10 per 1M tokens | $0.25/$1 per 1M tokens |
| Open weight? | No — API only | No — API only |
| Modalities | text, image, code | text, image, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Agentic workflows that plan, use tools, and run autonomously
Claude Sonnet 5
Claude Sonnet 5 lists agentic workflows that plan, use tools, and run autonomously among its strengths; Particle-1 does not.
Multi-step coding, debugging, and tool use
Claude Sonnet 5
Claude Sonnet 5 lists multi-step coding, debugging, and tool use among its strengths; Particle-1 does not.
Everyday professional and knowledge work
Claude Sonnet 5
Claude Sonnet 5 lists everyday professional and knowledge work among its strengths; Particle-1 does not.
Token-efficient coding model, post-trained with reinforcement learning on DeepSeek V4.1 Flash
Particle-1
Claude Sonnet 5 is comparatively weak here — an updated tokenizer that can use 1.0-1.35x more tokens for the same text
Particle reports 72.57% task pass rate versus 71.15% for DeepSeek V4.1 Flash, at $0.2211 versus $0.3368 per task
Particle-1
Particle AI's October 28, 2026 debut - a closed, token-efficient coding model post-trained on DeepSeek V4.1 Flash, with 1M context at $0.25/$1.00 at peak rates — and it runs cheaper at $0.25/$1 per 1M tokens.
Particle reports 28.4% to 52.2% fewer output tokens than the base model across four benchmarks
Particle-1
Particle AI's October 28, 2026 debut - a closed, token-efficient coding model post-trained on DeepSeek V4.1 Flash, with 1M context at $0.25/$1.00 at peak rates — and it is the newer of the two.
Lowest cost at scale
Particle-1
At $0.25/$1 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Particle-1
At $0.25/$1 per 1M tokens it undercuts Claude Sonnet 5, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Particle-1
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is agentic workflows that plan, use tools, and run autonomously
→ Claude Sonnet 5
It is specifically built for that.
Anyone whose priority is token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash
→ Particle-1
That is its strongest area.
Claude Sonnet 5: where it fits
Anthropic's most agentic Sonnet, with near-Opus-4.8 performance at Sonnet prices; the default model on Free and Pro. Released June 30, 2026 by Anthropic, it is built for agentic workflows that plan, use tools, and run autonomously, multi-step coding, debugging, and tool use, everyday professional and knowledge work, and long-document analysis and reasoning.
Its trade-offs are real: lower peak accuracy than Opus 4.8 on the hardest tasks, and an updated tokenizer that can use 1.0-1.35x more tokens for the same text. At $2 in / $10 out per million tokens, it sits in the mid price band.
Particle-1: where it fits
Particle AI's October 28, 2026 debut - a closed, token-efficient coding model post-trained on DeepSeek V4.1 Flash, with 1M context at $0.25/$1.00 at peak rates. Released October 28, 2026 by Particle AI, it is built for token-efficient coding model, post-trained with reinforcement learning on DeepSeek V4.1 Flash, particle reports 72.57% task pass rate versus 71.15% for DeepSeek V4.1 Flash, at $0.2211 versus $0.3368 per task, particle reports 28.4% to 52.2% fewer output tokens than the base model across four benchmarks, and peak API price of $0.25/$1.00 per million tokens, halved off-peak to $0.125/$0.50 (20:30-04:00 New York time).
Its trade-offs: aPI-only with no published weights, although its DeepSeek base model is open, all benchmarks are vendor-reported on Particle's own harness; none were independently reproduced as of October 31, and pricing is inconsistent across sources: Particle's launch post said $0.30/$1.20 and OpenRouter shows $0.05/$0.50, while its billing docs say $0.25/$1.00. At $0.25 in / $1 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Claude Sonnet 5 and Particle-1 overlap enough that the right pick depends on your specific job. Particle-1 costs less per token; Particle-1 holds the larger context; and each leads in its own area — Claude Sonnet 5 for agentic workflows that plan, use tools, and run autonomously, Particle-1 for token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Claude Sonnet 5 and Particle-1 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
See pricingFrequently asked questions
Is Claude Sonnet 5 or Particle-1 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Claude Sonnet 5 leans toward agentic workflows that plan, use tools, and run autonomously while Particle-1 leans toward token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Claude Sonnet 5 or Particle-1?
Particle-1 is cheaper — $2/$10 per 1M tokens vs $0.25/$1 per 1M tokens, roughly 8× apart on input.
Which has the bigger context window?
Effectively neither — 1M vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Claude Sonnet 5 and Particle-1 together?
Yes — a multi-model platform like LumiChats gives you Claude Sonnet 5, Particle-1 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Claude Sonnet 5 or Particle-1?
Particle-1 — released October 28, 2026, about 4 months after Claude Sonnet 5.
Related comparisons
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.