LLM Reference

Qwen3.5-27B vs TxGemma

Qwen3.5-27B (2026) and TxGemma (2024) are frontier reasoning models from Alibaba and Google DeepMind. Qwen3.5-27B ships a 262k-token context window, while TxGemma ships a not-yet-sourced 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.

Qwen3.5-27B is safer overall; choose TxGemma when provider fit matters.

Decision scorecard

Local evidence first
SignalQwen3.5-27BTxGemma
Best forreasoning-heavy apps, multimodal apps, and tool-calling agentstool-calling agents
Decision fitRAG, Agents, and Long contextAgents, Classification, and JSON / Tool use
Context window262k
Cheapest output$1.56/1M tokens-
Provider routes4 tracked1 tracked
Shared benchmarks0 rows0 rows

Decision tradeoffs

Choose Qwen3.5-27B when...
  • Qwen3.5-27B has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Qwen3.5-27B has broader tracked provider coverage for fallback and procurement flexibility.
  • Qwen3.5-27B uniquely exposes Vision, Multimodal, and Reasoning in local model data.
  • Local decision data tags Qwen3.5-27B for RAG, Agents, and Long context.
Choose TxGemma when...
  • 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.

Qwen3.5-27B

$546

Cheapest tracked route/tier: OpenRouter

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

Qwen3.5-27B -> TxGemma
  • No overlapping tracked provider route is sourced for Qwen3.5-27B and TxGemma; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Reasoning before moving production traffic.
TxGemma -> Qwen3.5-27B
  • No overlapping tracked provider route is sourced for TxGemma and Qwen3.5-27B; plan for SDK, billing, or endpoint changes.
  • Qwen3.5-27B adds Vision, Multimodal, and Reasoning in local capability data.

Specs

Specification
Released2026-02-242024-06-01
Context window262k
Parameters27B2B
Architecturedecoder onlydecoder only
LicenseApache 2.0Proprietary
Knowledge cutoff--

Pricing and availability

Pricing attributeQwen3.5-27BTxGemma
Input price$0.20/1M tokens-
Output price$1.56/1M tokens-
Providers

Capabilities

CapabilityQwen3.5-27BTxGemma
VisionYesNo
MultimodalYesNo
ReasoningYesNo
Function callingYesYes
Tool useYesYes
Structured outputsYesYes
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 vision: Qwen3.5-27B, multimodal input: Qwen3.5-27B, and reasoning mode: Qwen3.5-27B. Both models share function calling, tool use, and structured outputs, 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: Qwen3.5-27B has $0.20/1M input tokens and TxGemma has no token price sourced yet. Provider availability is 4 tracked routes versus 1. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Qwen3.5-27B when reasoning depth and broader provider choice 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 Qwen3.5-27B or TxGemma open source?

Qwen3.5-27B is listed under Apache 2.0. 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 vision, Qwen3.5-27B or TxGemma?

Qwen3.5-27B 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, Qwen3.5-27B or TxGemma?

Qwen3.5-27B 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 reasoning mode, Qwen3.5-27B or TxGemma?

Qwen3.5-27B has the clearer documented reasoning mode signal in this comparison. If reasoning mode 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, Qwen3.5-27B or TxGemma?

Both Qwen3.5-27B and TxGemma expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface. Use this as a quick comparison signal, then confirm the provider-specific limits before committing to production.

Where can I run Qwen3.5-27B and TxGemma?

Qwen3.5-27B is available on DeepInfra, OpenRouter, Alibaba Cloud PAI-EAS, and Novita AI. TxGemma is available on GCP Vertex AI. Provider coverage can affect latency, region availability, compliance posture, and fallback options.

Continue comparing

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