Claude Fable 5.1 vs Particle-1

Anthropic · US  |  Particle AI · US · Updated June 2026

Quick verdict

Pick Claude Fable 5.1 for terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) or cursorbench 3.2 agentic coding (73.4%). 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 Fable 5.1 (Anthropic) and Particle-1 (Particle AI) are two of the models people most often weigh against each other in 2026. Claude Fable 5.1 is anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. 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

Side-by-side specs

SpecClaude Fable 5.1Particle-1
ProviderAnthropic (US) Particle AI (US)
ReleasedSeptember 1, 2026 October 28, 2026
Context window1M tokens (~1,500 pages) 1M tokens (~1,573 pages)
Price (in/out)$10/$50 per 1M tokens $0.25/$1 per 1M tokens
Open weight?No — API only No — API only
Modalitiestext, image text, image, code
SWE-Bench VerifiedNot published Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%)

Claude Fable 5.1

Particle-1 is comparatively weak here — all benchmarks are vendor-reported on Particle's own harness; none were independently reproduced as of October 31

CursorBench 3.2 agentic coding (73.4%)

Claude Fable 5.1

Claude Fable 5.1 lists cursorBench 3.2 agentic coding (73.4%) among its strengths; Particle-1 does not.

Cache-read pricing cut to a quarter of other Claude models

Claude Fable 5.1

Particle-1 is comparatively weak here — 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

Token-efficient coding model, post-trained with reinforcement learning on DeepSeek V4.1 Flash

Particle-1

Claude Fable 5.1 is comparatively weak here — anthropic has not published an official SWE-bench Verified score for this model

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 Fable 5.1, 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 terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%)

→ Claude Fable 5.1

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 Fable 5.1: where it fits

Anthropic's September 1, 2026 update to its Fable line for coding and knowledge work, keeping the 1M-token context of Fable 5 while cutting cache-read costs and roughly doubling agentic-research benchmark scores. Released September 1, 2026 by Anthropic, it is built for terminal-Bench-Science agentic research (52.6%, more than double Fable 5's 24.7%), cursorBench 3.2 agentic coding (73.4%), cache-read pricing cut to a quarter of other Claude models, and long, multistep, document-heavy professional work with 1M-token context.

Its trade-offs are real: anthropic has not published an official SWE-bench Verified score for this model, restricted Mythos 5.1 variant outscores it on some benchmarks due to lighter safeguards (Terminal-Bench 4.0: 60.9% vs 55.8%), and closed weights, no self-hosting option. At $10 in / $50 out per million tokens, it sits in the premium 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 Fable 5.1 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 Fable 5.1 for terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%), 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 Fable 5.1 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 pricing

Frequently asked questions

Is Claude Fable 5.1 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 Fable 5.1 leans toward terminal-bench-science agentic research (52.6%, more than double fable 5's 24.7%) 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 Fable 5.1 or Particle-1?

Particle-1 is cheaper — $10/$50 per 1M tokens vs $0.25/$1 per 1M tokens, roughly 40× apart on input.

Which has the bigger context window?

Effectively neither — 1M tokens vs 1M tokens is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.

Can I use both Claude Fable 5.1 and Particle-1 together?

Yes — a multi-model platform like LumiChats gives you Claude Fable 5.1, 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 Fable 5.1 or Particle-1?

Particle-1 — released October 28, 2026, about 57 days after Claude Fable 5.1.

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.