LLM Reference

Stockmark 2 100B Instruct vs TxGemma

Stockmark 2 100B Instruct (2025) and TxGemma (2024) are compact production models from Stockmark and Google DeepMind. Stockmark 2 100B Instruct ships a 128K-token context window, while TxGemma ships a not-yet-sourced context window. This comparison covers specs, pricing, capabilities, benchmarks, provider availability, and production fit. It focuses on practical selection signals rather than broad model-family marketing. The goal is to make the tradeoff clear before deeper testing.

Stockmark 2 100B Instruct is safer overall; choose TxGemma when provider fit matters.

Decision scorecard

Local evidence first
SignalStockmark 2 100B InstructTxGemma
Best forgeneral production evaluationtool-calling agents
Decision fitLong contextAgents, Classification, and JSON / Tool use
Context window128K
Cheapest output--
Provider routes1 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Stockmark 2 100B Instruct when...
  • Stockmark 2 100B Instruct has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Stockmark 2 100B Instruct for Long context.
Choose TxGemma when...
  • TxGemma uniquely exposes Function calling, Tool use, and Structured outputs in local model data.
  • Local decision data tags TxGemma for Agents, Classification, and JSON / Tool use.

Monthly cost at traffic

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

Stockmark 2 100B Instruct

Unavailable

No complete token price in local provider data

TxGemma

Unavailable

No complete token price in local provider data

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

Switch friction

Stockmark 2 100B Instruct -> TxGemma
  • No overlapping tracked provider route is sourced for Stockmark 2 100B Instruct and TxGemma; plan for SDK, billing, or endpoint changes.
  • TxGemma adds Function calling, Tool use, and Structured outputs in local capability data.
TxGemma -> Stockmark 2 100B Instruct
  • No overlapping tracked provider route is sourced for TxGemma and Stockmark 2 100B Instruct; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Function calling, Tool use, and Structured outputs before moving production traffic.

Specs

Specification
Released2025-06-012024-06-01
Context window128K
Parameters100B2B
Architecturedecoder onlydecoder only
License1Proprietary
Knowledge cutoff--

Pricing and availability

Pricing attributeStockmark 2 100B InstructTxGemma
Input price--
Output price--
Providers

Pricing not yet sourced for either model.

Capabilities

CapabilityStockmark 2 100B InstructTxGemma
VisionNoNo
MultimodalNoNo
ReasoningNoNo
Function callingNoYes
Tool useNoYes
Structured outputsNoYes
Code executionNoNo
IDE integrationNoNo
Computer useNoNo
Parallel agentsNoNo

Benchmarks

No shared benchmark rows are currently sourced for this pair.

Deep dive

The capability footprint differs most on function calling: TxGemma, tool use: TxGemma, and structured outputs: TxGemma. 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: Stockmark 2 100B Instruct has no token price sourced yet and TxGemma has no token price sourced yet. Provider availability is 1 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Stockmark 2 100B Instruct when provider fit are central to the workload. Choose TxGemma 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 Stockmark 2 100B Instruct or TxGemma open source?

Stockmark 2 100B Instruct is listed under 1. TxGemma is listed under Proprietary. 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 function calling, Stockmark 2 100B Instruct or TxGemma?

TxGemma 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, Stockmark 2 100B Instruct or TxGemma?

TxGemma 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.

Which is better for structured outputs, Stockmark 2 100B Instruct or TxGemma?

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

Where can I run Stockmark 2 100B Instruct and TxGemma?

Stockmark 2 100B Instruct is available on NVIDIA NIM. TxGemma is available on GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

When should I pick Stockmark 2 100B Instruct over TxGemma?

Stockmark 2 100B Instruct is safer overall; choose TxGemma when provider fit matters. If your workload also depends on provider fit, start with Stockmark 2 100B Instruct; if it depends on provider fit, run the same evaluation with TxGemma.

Continue comparing

Last reviewed: 2026-05-22. Data sourced from public model cards and provider documentation.