Together AI - Gemma 3n-e4B vs GLM-5 9B
Together AI - Gemma 3n-e4B (2026) and GLM-5 9B (2026) are frontier reasoning models from Google DeepMind and Zhipu AI. Together AI - Gemma 3n-e4B ships a 8k-token context window, while GLM-5 9B ships a 262k-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.
GLM-5 9B fits 32x more tokens; pick it for long-context work and Together AI - Gemma 3n-e4B for tighter calls.
Decision scorecard
Local evidence first| Signal | Together AI - Gemma 3n-e4B | GLM-5 9B |
|---|---|---|
| Best for | tool-calling agents | reasoning-heavy apps and tool-calling agents |
| Decision fit | Agents, Classification, and JSON / Tool use | RAG, Agents, and Long context |
| Context window | 8k | 262k |
| Cheapest output | $0.04/1M tokens | - |
| Provider routes | 1 tracked | 0 tracked |
| Shared benchmarks | 0 rows | 0 rows |
Decision tradeoffs
- Together AI - Gemma 3n-e4B has broader tracked provider coverage for fallback and procurement flexibility.
- Together AI - Gemma 3n-e4B uniquely exposes Structured outputs in local model data.
- Local decision data tags Together AI - Gemma 3n-e4B for Agents, Classification, and JSON / Tool use.
- GLM-5 9B has the larger context window for long prompts, retrieval packs, or transcript analysis.
- GLM-5 9B uniquely exposes Reasoning in local model data.
- Local decision data tags GLM-5 9B for RAG, Agents, and Long context.
Monthly cost at traffic
Estimate token spend from the cheapest tracked input and output route or tier on this page.
Together AI - Gemma 3n-e4B
$26.00
Cheapest tracked route/tier: Together AI
GLM-5 9B
Unavailable
No complete token price in local provider data
Cost delta unavailable until both models have sourced input and output token prices.
Switch friction
- No overlapping tracked provider route is sourced for Together AI - Gemma 3n-e4B and GLM-5 9B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Structured outputs before moving production traffic.
- GLM-5 9B adds Reasoning in local capability data.
- No overlapping tracked provider route is sourced for GLM-5 9B and Together AI - Gemma 3n-e4B; plan for SDK, billing, or endpoint changes.
- Check replacement coverage for Reasoning before moving production traffic.
- Together AI - Gemma 3n-e4B adds Structured outputs in local capability data.
Specs
Pricing and availability
| Pricing attribute | Together AI - Gemma 3n-e4B | GLM-5 9B |
|---|---|---|
| Input price | $0.02/1M tokens | - |
| Output price | $0.04/1M tokens | - |
| Providers | - |
Capabilities
| Capability | Together AI - Gemma 3n-e4B | GLM-5 9B |
|---|---|---|
| Vision | No | No |
| Multimodal | No | No |
| Reasoning | No | Yes |
| Function calling | Yes | Yes |
| Tool use | Yes | Yes |
| Structured outputs | Yes | No |
| Code execution | No | No |
| IDE integration | No | No |
| Computer use | No | No |
| Parallel agents | No | No |
Benchmarks
No shared benchmark rows are currently sourced for this pair.
Deep dive
The capability footprint differs most on reasoning mode: GLM-5 9B and structured outputs: Together AI - Gemma 3n-e4B. Both models share function calling and tool use, 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: Together AI - Gemma 3n-e4B has $0.02/1M input tokens and GLM-5 9B 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 Together AI - Gemma 3n-e4B when provider fit and broader provider choice are central to the workload. Choose GLM-5 9B when reasoning depth and larger context windows 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.
FAQ
Which has a larger context window, Together AI - Gemma 3n-e4B or GLM-5 9B?
GLM-5 9B supports 262k tokens, while Together AI - Gemma 3n-e4B supports 8k tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.
Is Together AI - Gemma 3n-e4B or GLM-5 9B open source?
Together AI - Gemma 3n-e4B is listed under Gemma. GLM-5 9B is listed under MIT. 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 reasoning mode, Together AI - Gemma 3n-e4B or GLM-5 9B?
GLM-5 9B 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, Together AI - Gemma 3n-e4B or GLM-5 9B?
Both Together AI - Gemma 3n-e4B and GLM-5 9B expose function calling. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Which is better for tool use, Together AI - Gemma 3n-e4B or GLM-5 9B?
Both Together AI - Gemma 3n-e4B and GLM-5 9B expose tool use. The better choice depends on benchmark fit, context budget, pricing, and whether your provider route exposes the same capability surface.
Where can I run Together AI - Gemma 3n-e4B and GLM-5 9B?
Together AI - Gemma 3n-e4B is available on Together AI. GLM-5 9B is available on the tracked providers still being sourced. Provider coverage can affect latency, region availability, compliance posture, and fallback options.
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Last reviewed: 2026-05-11. Data sourced from public model cards and provider documentation.