Particle-1 vs Qwen 3.7 Max
Particle AI · US | Alibaba · China · 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 Qwen 3.7 Max for long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7) or 1m-token long-document and full-codebase analysis. On a tight budget at scale, Particle-1 is the value pick.
Particle-1 (Particle AI, US) and Qwen 3.7 Max (Alibaba, China) line up two different AI ecosystems against each other — a comparison that is as much about cost philosophy and openness as raw capability. 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. Qwen 3.7 Max is alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. 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 10× cheaper on input ($0.25/$1 per 1M tokens vs $2.5/$7.5 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
- ▸Context window: 1M tokens vs 1M — 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 5 months (released October 28, 2026), usually meaning fresher training data and capabilities.
- ▸Ecosystem: this is a US-vs-China matchup — they differ in pricing philosophy, data-residency options, and tooling ecosystems, not only benchmarks.
Side-by-side specs
| Spec | Particle-1 | Qwen 3.7 Max |
|---|---|---|
| Provider | Particle AI (US) | Alibaba (China) |
| Released | October 28, 2026 | May 20, 2026 |
| Context window | 1M tokens (~1,573 pages) | 1M (~1,500 pages) |
| Price (in/out) | $0.25/$1 per 1M tokens | $2.5/$7.5 per 1M tokens |
| Open weight? | No — API only | No — API only |
| 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
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 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 is the newer of the two.
Particle reports 28.4% to 52.2% fewer output tokens than the base model across four benchmarks
Particle-1
Particle-1 lists particle reports 28.4% to 52.2% fewer output tokens than the base model across four benchmarks among its strengths; Qwen 3.7 Max does not.
Long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7)
Qwen 3.7 Max
Particle-1 is comparatively weak here — all benchmarks are vendor-reported on Particle's own harness; none were independently reproduced as of October 31
1M-token long-document and full-codebase analysis
Qwen 3.7 Max
Qwen 3.7 Max lists 1M-token long-document and full-codebase analysis among its strengths; Particle-1 does not.
MCP tool orchestration and multi-hour autonomous runs
Qwen 3.7 Max
Qwen 3.7 Max lists mCP tool orchestration and multi-hour autonomous runs among its strengths; Particle-1 does not.
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 Qwen 3.7 Max, 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 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 long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7)
→ Qwen 3.7 Max
That is its strongest area.
An enterprise with regional data-residency rules
→ Particle-1 or Qwen 3.7 Max
Origin (US vs China) affects where data is processed and which compliance regime applies — check the provider's terms for your region.
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.
Qwen 3.7 Max: where it fits
Alibaba's agent-first frontier model — a 1M-token context and long-horizon coding at about half the cost of US flagships. Released May 20, 2026 by Alibaba, it is built for long-horizon agentic coding (SWE-Bench Pro 60.6, Terminal-Bench 2.0 69.7), 1M-token long-document and full-codebase analysis, mCP tool orchestration and multi-hour autonomous runs, and frontier intelligence at roughly half the price of US flagships.
Its trade-offs: text-only — no vision input (the Plus variant adds images), closed-weight, API-only — no self-hosting, trails GPT-5.5 and Claude Opus on the hardest one-shot reasoning, and chinese-jurisdiction data-residency considerations. At $2.5 in / $7.5 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
This is less "which is smarter" and more "which ecosystem fits." Particle-1 (US) and Qwen 3.7 Max (China) differ on pricing philosophy, data-residency, and tooling as much as on raw scores. Particle-1 is the cheaper option, which matters at volume. The pragmatic move is to run one real task through both and judge the outputs against your own constraints — including where your data is allowed to be processed.
Want both Particle-1 and Qwen 3.7 Max 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 Qwen 3.7 Max 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 Qwen 3.7 Max leans toward long-horizon agentic coding (swe-bench pro 60.6, terminal-bench 2.0 69.7), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Particle-1 or Qwen 3.7 Max?
Particle-1 is cheaper — $0.25/$1 per 1M tokens vs $2.5/$7.5 per 1M tokens, roughly 10× apart on input.
Which has the bigger context window?
Effectively neither — 1M tokens vs 1M is a difference of a few percent. Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Particle-1 and Qwen 3.7 Max together?
Yes — a multi-model platform like LumiChats gives you Particle-1, Qwen 3.7 Max 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 Qwen 3.7 Max?
Particle-1 — released October 28, 2026, about 5 months after Qwen 3.7 Max.
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.