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Head-to-head comparison

LFM2.5 Encoder 350M Diffusion vs llm jp 4 33b thinking

LFM2.5 Encoder 350M Diffusion (LiquidAI) and llm jp 4 33b thinking (Llm Jp) compared on the ModelCap Index, API price, context window, provider availability, weight access and every public benchmark board they share. Figures are the same ones shown on the live rankings; nothing here is a hidden score.

Snapshot as of 20 August 2026

As of 20 August 2026, LFM2.5 Encoder 350M Diffusion holds the stronger ModelCap Index position (#152 vs #153); and llm jp 4 33b thinking ships open weights.

Which should you choose?

Choose LFM2.5 Encoder 350M Diffusion if…

  • you want the stronger overall ModelCap Index position — #152 against #153 (21.7 vs 21.7 points).

Choose llm jp 4 33b thinking if…

  • you want to self-host: llm jp 4 33b thinking ships open weights while LFM2.5 Encoder 350M Diffusion is restricted license.
  • you want the more recently listed model — llm jp 4 33b thinking was listed 14 August 2026, LFM2.5 Encoder 350M Diffusion 10 July 2026.

LFM2.5 Encoder 350M Diffusion vs llm jp 4 33b thinking: specs, pricing and context

Specification comparison of LFM2.5 Encoder 350M Diffusion and llm jp 4 33b thinking
FieldLFM2.5 Encoder 350M DiffusionLiquidAIllm jp 4 33b thinkingLlm Jp
ModelCap Index position#152#153
Index score21.721.7
EvidenceEstimatedEstimated
Input price / 1M tokensUnlistedUnlisted
Output price / 1M tokensUnlistedUnlisted
Context window— tokens— tokens
Max output tokens——
API providers listed00
Weight accessRestricted licenseOpen weights
Input modalitiesTextText
First listed10 July 202614 August 2026
PublisherLiquidAILlm Jp

Evidence: global corpus prior · leave-one-anchor-out calibrated · global corpus prior · leave-one-anchor-out calibrated. Prices are the lowest listed API offer per million tokens observed on the OpenRouter catalogue.

Benchmark scores: LFM2.5 Encoder 350M Diffusion vs llm jp 4 33b thinking

Neither model has a published result on a public benchmark board ModelCap tracks yet.

Scores are the sources' own published figures for each model's best evaluated configuration; ModelCap never re-runs a benchmark.

Want a different pairing? Open the interactive comparison tool to swap either model for any current ranked language model.

LFM2.5 Encoder 350M Diffusion vs llm jp 4 33b thinking: common questions

Is LFM2.5 Encoder 350M Diffusion better than llm jp 4 33b thinking?

LFM2.5 Encoder 350M Diffusion ranks higher on the ModelCap Index as of 20 August 2026: #152 against #153. That is a capability ranking built from public benchmark evidence with published uncertainty; whether it is "better" for you also depends on price, context and where you can run it.

Is LFM2.5 Encoder 350M Diffusion cheaper than llm jp 4 33b thinking?

At least one of the two has no listed API price on ModelCap right now, so no price comparison is made.

Which has the bigger context window, LFM2.5 Encoder 350M Diffusion or llm jp 4 33b thinking?

Both publish a —-token context window.

Which is better for coding, LFM2.5 Encoder 350M Diffusion or llm jp 4 33b thinking?

The two models do not share a coding benchmark board on ModelCap yet, so no head-to-head coding score is published; the ModelCap Index position is the closest overall signal.

Are LFM2.5 Encoder 350M Diffusion and llm jp 4 33b thinking open-weight models?

LFM2.5 Encoder 350M Diffusion: Restricted license. llm jp 4 33b thinking: Open weights. Open weights mean the checkpoint can be downloaded and self-hosted under its licence; API-only models are available solely through hosted endpoints.

Where can I run LFM2.5 Encoder 350M Diffusion and llm jp 4 33b thinking?

ModelCap currently lists 0 API providers for LFM2.5 Encoder 350M Diffusion and 0 for llm jp 4 33b thinking, from the OpenRouter catalogue snapshot the site serves; each model page lists the providers and their prices.

How current is this LFM2.5 Encoder 350M Diffusion vs llm jp 4 33b thinking comparison?

Every figure comes from the sealed ModelCap dataset published 20 August 2026; the page re-renders within a minute of each data refresh, and the ModelCap Index positions are the same ones shown on the live rankings.

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