LLM·Dex

GPT-5 nano vs SmolLM2 1.7B

A complete head-to-head: pricing, context window, benchmarks, modality coverage, and openness, with a programmatic verdict synthesized from the underlying data.

Updated

GPT-5 nano specs · SmolLM2 1.7B specs
Verdict by category
  • PriceGPT-5 nano

    GPT-5 nano publishes pricing ($0.40 / 1M output tokens) while SmolLM2 1.7B does not.

  • Context windowGPT-5 nano

    GPT-5 nano accepts 400K tokens vs 8.2K, 48.8× the room for long documents and codebases.

  • BenchmarksTie

    No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores.

  • ModalitiesGPT-5 nano

    GPT-5 nano supports 2 modalities (text, vision) vs 1 for SmolLM2 1.7B.

  • OpennessSmolLM2 1.7B

    SmolLM2 1.7B ships open weights (Apache-2.0); GPT-5 nano is API-only.

On balance GPT-5 nano edges ahead, winning 3 of 5 categories against SmolLM2 1.7B's 1. GPT-5 nano publishes pricing ($0.40 / 1M output tokens) while SmolLM2 1.7B does not. GPT-5 nano accepts 400K tokens vs 8.2K, 48.8× the room for long documents and codebases.

No directly comparable public benchmarks are available for both models, check the spec sheets for individual scores. They differ in modality coverage, GPT-5 nano handles text, vision while SmolLM2 1.7B handles text, which can be the deciding factor before you even look at benchmarks. SmolLM2 1.7B ships open weights (Apache-2.0); GPT-5 nano is API-only.

GPT-5 nano is the newer of the two, released 9 months after SmolLM2 1.7B, which usually means a more recent knowledge cutoff and updated safety post-training. GPT-5 nano is usually picked for cheapest llm and fastest llm workloads, while SmolLM2 1.7B sees more deployments in on device and edge deployment. If pricing matters more than every last benchmark point, run the numbers in the calculator below before committing.

Side-by-side specs

SpecGPT-5 nanoSmolLM2 1.7B
ProviderOpenAIOther
ReleasedAug 2025Nov 2024
Modalitiestext, visiontext
Context window400K tokens8.2K tokens
Max output128K tokens,
Input · 1M$0.050 / 1M tokensPricing not published
Output · 1M$0.40 / 1M tokensPricing not published
Knowledge cutoff2024-09,
Open weightsNoYes (Apache-2.0)
API availableYesNo

Pricing at scale

What you'd actually pay at typical workloads. Numbers come from each model's published per-million-token rates.

  • Light usage, 100k in / 50k out per day$0.750 vs ,
  • Heavy usage, 1M in / 500k out per day$7.50 vs ,
  • RAG workload, 5M in / 200k out per day$9.90 vs ,

Light usage, 100k in / 50k out per day: pricing not directly comparable (one or both models are missing public per-token rates). Heavy usage, 1M in / 500k out per day: pricing not directly comparable (one or both models are missing public per-token rates). RAG workload, 5M in / 200k out per day: pricing not directly comparable (one or both models are missing public per-token rates).

Price calculator

Estimated spend for the listed models at your usage. Numbers are derived from each model's published per-million-token rates.

  • GPT-5 nano$0.025
  • SmolLM2 1.7BPricing unavailable

Benchmarks compared

Only sourced numbers. Where a benchmark is missing for one model we show the available value rather than fabricating the other.

Benchmark scores not yet available. We only publish numbers we can source from official model cards or independent leaderboards, see methodology.
Pick GPT-5 nano if

GPT-5 nano fits when…

  • Lowest-cost OpenAI model with vision support
  • Fast P99 latency
  • Good enough for routing and classification
  • Long-context tasks, handles 400K tokens vs 8.2K for SmolLM2 1.7B.
  • Multimodal needs covering vision.
Pick SmolLM2 1.7B if

SmolLM2 1.7B fits when…

  • Truly tiny
  • Apache-2.0
  • Runs on phones
  • Self-hosting and on-prem requirements, open weights (Apache-2.0).
Don't want either?

Consider GPT-5.5

OpenAI's mid-cycle GPT-5 refresh, improved reasoning, tool use, and multimodal grounding over the 2025 launch.

Frequently asked

  • Is GPT-5 nano or SmolLM2 1.7B cheaper?
    Per-token pricing isn't published for at least one of these models, check each model's spec page for current rates.
  • Which has the larger context window?
    GPT-5 nano accepts 400K tokens vs 8.2K for SmolLM2 1.7B.
  • Is GPT-5 nano or SmolLM2 1.7B better for coding?
    Both GPT-5 nano and SmolLM2 1.7B are competitive on coding benchmarks. See each model's individual spec page for HumanEval and SWE-bench scores where published. For an opinionated pick, consult our Best LLM for Coding ranking.
  • Are either of these models open source?
    SmolLM2 1.7B ships open weights (Apache-2.0). GPT-5 nano is API-only.
  • When were GPT-5 nano and SmolLM2 1.7B released?
    GPT-5 nano was released by OpenAI on 2025-08-07. SmolLM2 1.7B was released by Other on 2024-11-01.
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