Grok Code Fast 1 vs LFM3-1.7B
xAI · US | Liquid AI · US · Updated June 2026
Quick verdict
Pick Grok Code Fast 1 for fast, cheap agentic coding at $0.20/$1.50 or low-latency code generation and terminal tasks. Pick LFM3-1.7B for very small open-weight text model - about 1.73b parameters with a 256k-token context for on-device use or liquid says it can power agentic applications that used to need 9b parameters. Choose LFM3-1.7B if you need self-hosting or data privacy; Grok Code Fast 1 if you want a managed API.
Grok Code Fast 1 (xAI) and LFM3-1.7B (Liquid AI) are two of the models people most often weigh against each other in 2026. Grok Code Fast 1 is xAI's speed-tier coding model at $0.20/$1.50 with a 256K window — cheap, fast agentic code over frontier quality. LFM3-1.7B is liquid AI's October 27, 2026 on-device text model - about 1.73B parameters and 256K context, with open weights under a license capped at $10M annual revenue. They diverge most on price and open vs. closed weights — each quantified below from the models' real specs.
Key differences at a glance
- ▸Cost model: LFM3-1.7B ships open weights you can self-host (hardware cost only, no per-token fee), while Grok Code Fast 1 is API-metered at $0.2/$1.5 per 1M tokens. Your choice depends on whether you want zero marginal cost at the price of running infrastructure.
- ▸Context window: both advertise 256K (~384 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
- ▸Recency: LFM3-1.7B is the newer model by about 14 months (released October 27, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
| Spec | Grok Code Fast 1 | LFM3-1.7B |
|---|---|---|
| Provider | xAI (US) | Liquid AI (US) |
| Released | August 28, 2025 | October 27, 2026 |
| Context window | 256K (~384 pages) | 256K tokens (~384 pages) |
| Price (in/out) | $0.2/$1.5 per 1M tokens | Open weight (self-host / free) |
| Open weight? | No — API only | Yes — self-hostable |
| Modalities | text, code | text |
| SWE-Bench Verified | Not published | Not published |
| MRCR v2 @ 1M | Not published | Not published |
Who wins what
Fast, cheap agentic coding at $0.20/$1.50
Grok Code Fast 1
LFM3-1.7B is comparatively weak here — liquid says it is not recommended for agentic coding or complex multi-step reasoning because of its size
Low-latency code generation and terminal tasks
Grok Code Fast 1
Grok Code Fast 1 lists low-latency code generation and terminal tasks among its strengths; LFM3-1.7B does not.
High-volume coding pipelines where speed beats peak quality
Grok Code Fast 1
Grok Code Fast 1 lists high-volume coding pipelines where speed beats peak quality among its strengths; LFM3-1.7B does not.
Very small open-weight text model - about 1.73B parameters with a 256K-token context for on-device use
LFM3-1.7B
Open weights make this possible at all — Grok Code Fast 1 is API-only, so it cannot leave the vendor's servers.
Liquid says it can power agentic applications that used to need 9B parameters
LFM3-1.7B
Liquid AI's October 27, 2026 on-device text model - about 1.73B parameters and 256K context, with open weights under a license capped at $10M annual revenue — and its weights are open while Grok Code Fast 1 is API-only.
Part of a six-model LFM3 family covering text, vision, audio, omni and decision tasks
LFM3-1.7B
Grok Code Fast 1 is comparatively weak here — text and code only — no image, audio or video input
Lowest cost at scale
LFM3-1.7B
Its weights are open, so at volume you pay for your own hardware instead of Grok Code Fast 1's $0.2/$1.5 per 1M tokens.
Which should you pick?
A cost-sensitive startup shipping high volume
→ LFM3-1.7B
At Open weight (self-host / free) it undercuts Grok Code Fast 1, and on millions of tokens that margin decides the monthly bill.
A team with data-privacy or self-hosting needs
→ LFM3-1.7B
Open weights let you run it on your own hardware; Grok Code Fast 1 is API-only.
Anyone whose priority is fast, cheap agentic coding at $0.20/$1.50
→ Grok Code Fast 1
It is specifically built for that.
Anyone whose priority is very small open-weight text model - about 1.73b parameters with a 256k-token context for on-device use
→ LFM3-1.7B
That is its strongest area.
Grok Code Fast 1: where it fits
XAI's speed-tier coding model at $0.20/$1.50 with a 256K window — cheap, fast agentic code over frontier quality. Released August 28, 2025 by xAI, it is built for fast, cheap agentic coding at $0.20/$1.50, low-latency code generation and terminal tasks, high-volume coding pipelines where speed beats peak quality, and a 256K window sized for real codebases.
Its trade-offs are real: text and code only — no image, audio or video input, xAI did not publish a SWE-Bench Verified score, a speed-tier coding model, not a frontier reasoner, and narrow focus — built for code, not general knowledge work. At $0.2 in / $1.5 out per million tokens, it sits in the budget price band.
LFM3-1.7B: where it fits
Liquid AI's October 27, 2026 on-device text model - about 1.73B parameters and 256K context, with open weights under a license capped at $10M annual revenue. Released October 27, 2026 by Liquid AI, it is built for very small open-weight text model - about 1.73B parameters with a 256K-token context for on-device use, liquid says it can power agentic applications that used to need 9B parameters, part of a six-model LFM3 family covering text, vision, audio, omni and decision tasks, and supports 16 languages.
Its trade-offs: lFM Open License v1.0 covers commercial use only below $10M annual revenue; larger firms need a paid license, liquid says it is not recommended for agentic coding or complex multi-step reasoning because of its size, text-only; vision and audio need other LFM3 checkpoints, and no published per-token API price found. 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. LFM3-1.7B gives you weights you control — self-host it, fine-tune it, keep data in-house, pay only for hardware. Grok Code Fast 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 Grok Code Fast 1 and LFM3-1.7B 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 Grok Code Fast 1 or LFM3-1.7B 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, Grok Code Fast 1 leans toward fast, cheap agentic coding at $0.20/$1.50 while LFM3-1.7B leans toward very small open-weight text model - about 1.73b parameters with a 256k-token context for on-device use, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Grok Code Fast 1 or LFM3-1.7B?
LFM3-1.7B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Grok Code Fast 1 is API-metered at $0.2/$1.5 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?
Both advertise 256K (~384 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Can I use both Grok Code Fast 1 and LFM3-1.7B together?
Yes — a multi-model platform like LumiChats gives you Grok Code Fast 1, LFM3-1.7B 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, Grok Code Fast 1 or LFM3-1.7B?
LFM3-1.7B — released October 27, 2026, about 14 months after Grok Code Fast 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.