API cost decision in 10 seconds

NewLFM3-1.7B vs DeepSeek V4.1 Flash (batch)

Pick LFM3-1.7B for lower cost; pick DeepSeek V4.1 Flash (batch) only if the larger context window matters more.

Page updated:  Data confirmed:  Prices normalized to USD per 1M tokens Sample workload: 1M input + 500K output

Budget verdict

Pick LFM3-1.7B for lower cost; pick DeepSeek V4.1 Flash (batch) only if the larger context window matters more.

On the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $0.28 for DeepSeek V4.1 Flash (batch), saving $0.1 (35.7% lower).

Cost-first pickLFM3-1.7B
Context-first pickDeepSeek V4.1 Flash (batch)
Sample savings$0.135.7%
10x traffic gap$1

DeepSeek V4.1 Flash (batch) has more context, but LFM3-1.7B saves $0.1 on the standard workload. At 10x that traffic, the same price gap is about $1. Use the calculator below to replace the sample workload with your own token volume.

Cost sensitivity

Workload Sensitivity

Same prices, different token mixes.

LFM3-1.7B stays cheaper across input-heavy, balanced, and output-heavy sample workloads.

Workload shapeToken mixBetter pickLFM3-1.7BDeepSeek V4.1 Flash (batch)
Input-heavy / RAG5M input + 500K outputLFM3-1.7B$0.5$0.73
Balanced workload1M input + 1M outputLFM3-1.7B$0.28$0.45
Output-heavy chatbot1M input + 5M outputLFM3-1.7B$1.08$1.79
Cheaper input LFM3-1.7B $0.08 vs $0.112 / 1M

LFM3-1.7B is $0.03 cheaper per 1M input tokens (28.6% lower; 1.4x difference).

Cheaper output LFM3-1.7B $0.2 vs $0.336 / 1M

LFM3-1.7B is $0.14 cheaper per 1M output tokens (40.5% lower; 1.68x difference).

Larger context DeepSeek V4.1 Flash (batch) 262.14K vs 1.05M

DeepSeek V4.1 Flash (batch) has 786.43K more context (4x larger).

Sample workload LFM3-1.7B $0.18 vs $0.28

LFM3-1.7B is $0.1 cheaper on the standard workload (35.7% lower).

Estimate your workload cost

Your Workload Cost

Prices are normalized to USD per 1M tokens.
LFM3-1.7B Calculating… Estimated API cost
DeepSeek V4.1 Flash (batch) Calculating… Estimated API cost
Cheaper for this workload Calculating… Difference: calculating…

This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.

Quick Decision

Verdict

LFM3-1.7B has the lower input price; LFM3-1.7B has the lower output price; DeepSeek V4.1 Flash (batch) offers the larger context window. For the 1M input plus 500K output sample, LFM3-1.7B is cheaper for the standard workload.

For a 1M input token plus 500K output token workload, the estimated API cost is $0.18 for LFM3-1.7B and $0.28 for DeepSeek V4.1 Flash (batch).

Best Fit

Choose LFM3-1.7B when you care most about lower input-token price, and lower output-token price.

Choose DeepSeek V4.1 Flash (batch) when you care most about larger context window.

Decision Notes
  • On the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $0.28 for DeepSeek V4.1 Flash (batch), saving $0.1 (35.7% lower).
  • LFM3-1.7B is $0.1 cheaper on the standard workload (35.7% lower).
  • LFM3-1.7B is $0.03 cheaper per 1M input tokens (28.6% lower; 1.4x difference).
  • LFM3-1.7B is $0.14 cheaper per 1M output tokens (40.5% lower; 1.68x difference).
  • DeepSeek V4.1 Flash (batch) has 786.43K more context (4x larger).
Head-to-Head Specs
FeatureNewLFM3-1.7B
(LiquidAI)
DeepSeek V4.1 Flash (batch)
(DeepSeek)
Input Price
prompt tokens per 1M
$0.08$0.112
Completion Price
per 1M tokens
$0.2$0.336
Sample Workload Cost
1M input + 500K output
$0.18$0.28
Context Window262.14K1.05M
Release Date

Use-Case Decision Matrix

Use caseBetter pickWhy
Budget-constrained productionLFM3-1.7BOn the standard 1M input plus 500K output workload, LFM3-1.7B is estimated at $0.18 vs $0.28 for DeepSeek V4.1 Flash (batch), saving $0.1 (35.7% lower).
High-volume input processingLFM3-1.7BLower prompt-token price matters most when prompts, retrieved passages, or documents dominate the bill.
Long responses and chatbotsLFM3-1.7BLower output-token price matters most when assistants generate many completion tokens.
RAG or long-document workDeepSeek V4.1 Flash (batch)A larger context window leaves more room for retrieved passages, conversation history, or source files.

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Provider catalogs

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LiquidAI catalog

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DeepSeek catalog

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LFM3-1.7B

A compact 1.7B-parameter text model with a 256K-token context, post-trained for agents, tool calling, and structured outputs. It reasons before it answers. Prompts and outputs may be retained and used...

DeepSeek V4.1 Flash (batch)

DeepSeek V4.1 Flash is a sparse mixture-of-experts model from DeepSeek, and the first built on the company's Causal Encoder-Decoder (CED) architecture. It activates 8B parameters on input and 16B on...