Particle-1 vs Reka Flash 3.1
Particle AI · US | Reka AI · US · Updated June 2026
Quick verdict
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. Pick Reka Flash 3.1 for a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists) or strong base for fine-tuning agentic tasks - notably improved coding since the original flash 3. Choose Reka Flash 3.1 if you need self-hosting or data privacy; Particle-1 if you want a managed API.
Particle-1 (Particle AI) and Reka Flash 3.1 (Reka AI) are two of the models people most often weigh against each other in 2026. 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. Reka Flash 3.1 is reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. They diverge most on price, context window and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Cost model: Reka Flash 3.1 ships open weights you can self-host (hardware cost only, no per-token fee), while Particle-1 is API-metered at $0.25/$1 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: Particle-1 holds 32× more — 1M tokens (~1,573 pages) vs 32K (~49 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
- ▸Recency: Particle-1 is the newer model by about 16 months (released October 28, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Particle-1 | Reka Flash 3.1 |
|---|---|---|
| Provider | Particle AI (US) | Reka AI (US) |
| Released | October 28, 2026 | July 2025 |
| Context window | 1M tokens (~1,573 pages) | 32K (~49 pages) |
| Price (in/out) | $0.25/$1 per 1M tokens | Open weight (self-host / free) |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, image, code | text, code |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Token-efficient coding model, post-trained with reinforcement learning on DeepSeek V4.1 Flash
Particle-1
Its 1M tokens window holds about 32× more than Reka Flash 3.1's 32K in a single prompt.
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 carries the larger 1M tokens context.
Particle reports 28.4% to 52.2% fewer output tokens than the base model across four benchmarks
Particle-1
Reka Flash 3.1 is comparatively weak here — a relatively small 32K context window next to million-token frontier models
A 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists)
Reka Flash 3.1
Open weights make this possible at all — Particle-1 is API-only, so it cannot leave the vendor's servers.
Strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3
Reka Flash 3.1
Reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni — and its weights are open while Particle-1 is API-only.
Fully open weights (Apache 2.0) from a frontier-caliber research team
Reka Flash 3.1
Particle-1 is comparatively weak here — aPI-only with no published weights, although its DeepSeek base model is open
Lowest cost at scale
Reka Flash 3.1
Its weights are open, so at volume you pay for your own hardware instead of Particle-1's $0.25/$1 per 1M tokens.
Largest single-prompt input
Particle-1
Its 1M tokens window is about 32× larger than Reka Flash 3.1's 32K, fitting roughly 1,573 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Reka Flash 3.1
At Open weight (self-host / free) it undercuts Particle-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.
A team with data-privacy or self-hosting needs
→ Reka Flash 3.1
Open weights let you run it on your own hardware; Particle-1 is API-only.
Anyone whose priority is token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash
→ Particle-1
It is specifically built for that.
Anyone whose priority is a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists)
→ Reka Flash 3.1
That is its strongest area.
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 are real: 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.
Reka Flash 3.1: where it fits
Reka AI's compact 21B open-weight reasoning model - small enough to run locally, from a team of DeepMind and Meta alumni. Released July 2025 by Reka AI, it is built for a 21B-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), strong base for fine-tuning agentic tasks - notably improved coding since the original Flash 3, fully open weights (Apache 2.0) from a frontier-caliber research team, and built by alumni from Google DeepMind and Meta's AI labs.
Its trade-offs: a relatively small 32K context window next to million-token frontier models, smaller and less capable overall than flagship frontier models from major labs, and reka's broader roadmap has shifted toward robotics/world models after merging with Moonvalley in June 2026, raising questions about ongoing LLM investment. As an open-weight model, its running cost is your own hardware rather than a per-token fee.
The bottom line for this matchup
The defining split here is open vs. closed. Reka Flash 3.1 gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Particle-1 gives you a managed, always-updated API with no infrastructure to run. Teams with GPUs, privacy requirements, or huge volume often favour the open model; teams that want zero ops and the latest capabilities favour the closed one. Capability is close enough that this operational question, not the benchmark, usually decides it.
Want both Particle-1 and Reka Flash 3.1 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 Particle-1 or Reka Flash 3.1 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, Particle-1 leans toward token-efficient coding model, post-trained with reinforcement learning on deepseek v4.1 flash while Reka Flash 3.1 leans toward a 21b-parameter reasoning model, small enough for local/on-device deployment (a 3.5-bit quantized build exists), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Particle-1 or Reka Flash 3.1?
Reka Flash 3.1 is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Particle-1 is API-metered at $0.25/$1 per 1M tokens. For most teams without GPUs, the API model is cheaper to start; at very high volume, self-hosting can win.
Which has the bigger context window?
Particle-1 — 1M tokens vs 32K, about 32× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Particle-1 and Reka Flash 3.1 together?
Yes — a multi-model platform like LumiChats gives you Particle-1, Reka Flash 3.1 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, Particle-1 or Reka Flash 3.1?
Particle-1 — released October 28, 2026, about 16 months after Reka Flash 3.1.
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.