Claude Haiku 4.5 vs LFM3-1.7B

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

Quick verdict

Pick Claude Haiku 4.5 for fastest claude model or near-frontier coding for its tier — 73.3% on swe-bench verified. 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; Claude Haiku 4.5 if you want a managed API.

Claude Haiku 4.5 (Anthropic) and LFM3-1.7B (Liquid AI) are two of the models people most often weigh against each other in 2026. Claude Haiku 4.5 is anthropic's fastest, most compact model — built for speed and volume. 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, context window and open vs. closed weights — each quantified below from the models' real specs.

Key differences at a glance

Side-by-side specs

SpecClaude Haiku 4.5LFM3-1.7B
ProviderAnthropic (US) Liquid AI (US)
ReleasedOctober 15, 2025 October 27, 2026
Context window200K (~300 pages) 256K tokens (~384 pages)
Price (in/out)$1/$5 per 1M tokens Open weight (self-host / free)
Open weight?No — API only Yes — self-hostable
Modalitiestext, image, code text
SWE-Bench Verified73.3% Not published
MRCR v2 @ 1MNot published Not published

Who wins what

Fastest Claude model

Claude Haiku 4.5

Claude Haiku 4.5 lists fastest Claude model among its strengths; LFM3-1.7B does not.

Near-frontier coding for its tier — 73.3% on SWE-Bench Verified

Claude Haiku 4.5

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, high-volume API calls

Claude Haiku 4.5

Claude Haiku 4.5 lists low-latency, high-volume API calls 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

Its 256K tokens window holds about 1.3× more than Claude Haiku 4.5's 200K in a single prompt.

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 it carries the larger 256K tokens context.

Part of a six-model LFM3 family covering text, vision, audio, omni and decision tasks

LFM3-1.7B

Claude Haiku 4.5 is comparatively weak here — smallest context in the family (200K)

Lowest cost at scale

LFM3-1.7B

Its weights are open, so at volume you pay for your own hardware instead of Claude Haiku 4.5's $1/$5 per 1M tokens.

Largest single-prompt input

LFM3-1.7B

Its 256K tokens window is about 1.3× larger than Claude Haiku 4.5's 200K, fitting roughly 384 pages in one prompt.

Which should you pick?

A cost-sensitive startup shipping high volume

→ LFM3-1.7B

At Open weight (self-host / free) it undercuts Claude Haiku 4.5, and on millions of tokens that margin decides the monthly bill.

Someone analysing very long documents or codebases

→ LFM3-1.7B

Larger 256K tokens window fits more in one prompt.

A team with data-privacy or self-hosting needs

→ LFM3-1.7B

Open weights let you run it on your own hardware; Claude Haiku 4.5 is API-only.

Anyone whose priority is fastest claude model

→ Claude Haiku 4.5

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.

Claude Haiku 4.5: where it fits

Anthropic's fastest, most compact model — built for speed and volume. Released October 15, 2025 by Anthropic, it is built for fastest Claude model, near-frontier coding for its tier — 73.3% on SWE-Bench Verified, low-latency, high-volume API calls, and cheapest Claude tier at $1/$5.

Its trade-offs are real: smallest context in the family (200K), and not for deep reasoning. At $1 in / $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. Claude Haiku 4.5 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 Claude Haiku 4.5 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 pricing

Frequently asked questions

Is Claude Haiku 4.5 or LFM3-1.7B better for coding?

Public SWE-Bench figures are not available for LFM3-1.7B, so the honest test is your own repository — run an identical real bug through both. By design, Claude Haiku 4.5 leans toward fastest claude model 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, Claude Haiku 4.5 or LFM3-1.7B?

LFM3-1.7B is open-weight, so self-hosting means no per-token fee (you pay for hardware instead), while Claude Haiku 4.5 is API-metered at $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?

LFM3-1.7B — 256K tokens vs 200K, about 1.3× larger. Useful only if the model actually reasons over the full window, which not all do.

Can I use both Claude Haiku 4.5 and LFM3-1.7B together?

Yes — a multi-model platform like LumiChats gives you Claude Haiku 4.5, 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, Claude Haiku 4.5 or LFM3-1.7B?

LFM3-1.7B — released October 27, 2026, about 13 months after Claude Haiku 4.5.

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.