LLM Reference

MedGemma vs Swallow 13B Instruct

MedGemma (2024) and Swallow 13B Instruct (2024) are compact production models from Google DeepMind and Tokyo Institute of Technology. MedGemma ships a not-yet-sourced context window, while Swallow 13B Instruct ships a 8k-token context window. This comparison covers specs, pricing, API access, capabilities, benchmarks, input and output token costs, and production fit for coding and agent workloads. It focuses on practical selection signals rather than broad model-family marketing.

Swallow 13B Instruct is safer overall; choose MedGemma when vision-heavy evaluation matters.

Decision scorecard

Local evidence first
SignalMedGemmaSwallow 13B Instruct
Best formultimodal apps and tool-calling agentsgeneral production evaluation
Decision fitAgents, Vision, and JSON / Tool useGeneral
Context window8k
Cheapest output--
Provider routes1 tracked0 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose MedGemma when...
  • MedGemma has broader tracked provider coverage for fallback and procurement flexibility.
  • MedGemma uniquely exposes Vision, Multimodal, and Function calling in local model data.
  • Local decision data tags MedGemma for Agents, Vision, and JSON / Tool use.
Choose Swallow 13B Instruct when...
  • Swallow 13B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.

Monthly cost at traffic

Estimate token spend from the cheapest tracked input and output route or tier on this page.

MedGemma

Unavailable

No complete token price in local provider data

Swallow 13B Instruct

Unavailable

No complete token price in local provider data

Cost delta unavailable until both models have sourced input and output token prices.

Switch friction

MedGemma -> Swallow 13B Instruct
  • No overlapping tracked provider route is sourced for MedGemma and Swallow 13B Instruct; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Function calling before moving production traffic.
Swallow 13B Instruct -> MedGemma
  • No overlapping tracked provider route is sourced for Swallow 13B Instruct and MedGemma; plan for SDK, billing, or endpoint changes.
  • MedGemma adds Vision, Multimodal, and Function calling in local capability data.

Specs

Specification
Released2024-07-012024-12-10
Context window8k
Parameters4B13B
ArchitectureDecoder Only-
LicenseProprietaryLlama 2 Community
OpennessProprietaryOpen weights
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff-2023

Pricing and availability

Pricing attributeMedGemmaSwallow 13B Instruct
Input price--
Output price--
Providers-

Pricing not yet sourced for either model.

Capabilities

CapabilityMedGemmaSwallow 13B Instruct
VisionYesNo
MultimodalYesNo
ReasoningNoNo
Function callingYesNo
Tool useYesNo
Structured outputsYesNo
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark scores are currently available for this pair.

Deep dive

The capability footprint differs most on vision: MedGemma, multimodal input: MedGemma, function calling: MedGemma, tool use: MedGemma, and structured outputs: MedGemma. Both models share the core language-model surface, so the practical split is not just feature count. Use those differences to decide whether the page is about raw model quality, agentic coding support, multimodal ingestion, or predictable structured API behavior.

Pricing coverage is uneven: MedGemma has no token price sourced yet and Swallow 13B Instruct has no token price sourced yet. Provider availability is 1 tracked routes versus 0. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose MedGemma when vision-heavy evaluation and broader provider choice are central to the workload. Choose Swallow 13B Instruct when provider fit are more important. For production, rerun your own prompts through the exact provider, region, and tool stack you plan to ship. This keeps the decision grounded in measurable tradeoffs instead of brand-level assumptions. It also helps separate model capability from provider packaging, which can change cost and latency. For teams standardizing a stack, that distinction is often the difference between a benchmark win and a reliable deployment.

FAQ

Is MedGemma or Swallow 13B Instruct open source?

MedGemma is listed under Proprietary. Swallow 13B Instruct is listed under Llama 2 Community. License labels affect whether you can self-host, redistribute weights, or rely only on hosted APIs, so confirm the upstream license before deployment.

Which is better for vision, MedGemma or Swallow 13B Instruct?

MedGemma has the clearer documented vision signal in this comparison. If vision is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Which is better for multimodal input, MedGemma or Swallow 13B Instruct?

MedGemma has the clearer documented multimodal input signal in this comparison. If multimodal input is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for function calling, MedGemma or Swallow 13B Instruct?

MedGemma has the clearer documented function calling signal in this comparison. If function calling is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Which is better for tool use, MedGemma or Swallow 13B Instruct?

MedGemma has the clearer documented tool use signal in this comparison. If tool use is mission-critical, validate it against the provider endpoint because model-level support and API-level exposure can differ.

Where can I run MedGemma and Swallow 13B Instruct?

MedGemma is available on GCP Vertex AI. Swallow 13B Instruct is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

Last reviewed: 2026-06-15. Data sourced from public model cards and provider documentation.