LLM Reference

Gemini 1.5 Pro 002 vs Llama 4 Maverick 17B Instruct FP8

Gemini 1.5 Pro 002 (2024) and Llama 4 Maverick 17B Instruct FP8 (2025) are general-purpose language models from Google DeepMind and AI at Meta. Gemini 1.5 Pro 002 ships a 2m-token context window, while Llama 4 Maverick 17B Instruct FP8 ships a 1m-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.

Llama 4 Maverick 17B Instruct FP8 is safer overall; choose Gemini 1.5 Pro 002 when long-context analysis matters.

Decision scorecard

Local evidence first
SignalGemini 1.5 Pro 002Llama 4 Maverick 17B Instruct FP8
Best forlong-context analysismultimodal apps, long-context analysis, and provider-routed production
Decision fitLong contextCoding, RAG, and Agents
Context window2m1m
Cheapest output-$0.60/1M tokens
Provider routes0 tracked10 tracked
Shared benchmarks0 shared0 shared

Decision tradeoffs

Choose Gemini 1.5 Pro 002 when...
  • Gemini 1.5 Pro 002 has the larger context window for long prompts, retrieval packs, or transcript analysis.
  • Local decision data tags Gemini 1.5 Pro 002 for Long context.
Choose Llama 4 Maverick 17B Instruct FP8 when...
  • Llama 4 Maverick 17B Instruct FP8 has broader tracked provider coverage for fallback and procurement flexibility.
  • Llama 4 Maverick 17B Instruct FP8 uniquely exposes Vision, Multimodal, and Structured outputs in local model data.
  • Local decision data tags Llama 4 Maverick 17B Instruct FP8 for Coding, RAG, and Agents.

Monthly cost at traffic

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

Gemini 1.5 Pro 002

Unavailable

No complete token price in local provider data

Llama 4 Maverick 17B Instruct FP8

$270

Cheapest tracked route/tier: OpenRouter

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

Switch friction

Gemini 1.5 Pro 002 -> Llama 4 Maverick 17B Instruct FP8
  • No overlapping tracked provider route is sourced for Gemini 1.5 Pro 002 and Llama 4 Maverick 17B Instruct FP8; plan for SDK, billing, or endpoint changes.
  • Llama 4 Maverick 17B Instruct FP8 adds Vision, Multimodal, and Structured outputs in local capability data.
Llama 4 Maverick 17B Instruct FP8 -> Gemini 1.5 Pro 002
  • No overlapping tracked provider route is sourced for Llama 4 Maverick 17B Instruct FP8 and Gemini 1.5 Pro 002; plan for SDK, billing, or endpoint changes.
  • Check replacement coverage for Vision, Multimodal, and Structured outputs before moving production traffic.

Specs

Specification
Released2024-09-242025-04-05
Context window2m1m
Parameters400B (17B active)
ArchitectureDecoder OnlyMixture of Experts
LicenseProprietaryLlama 4 Community
OpennessProprietaryOpen weights
Commercial useCommercial use: conditionalCommercial use: conditional
Knowledge cutoff2024-082024-08

Pricing and availability

Pricing attributeGemini 1.5 Pro 002Llama 4 Maverick 17B Instruct FP8
Input price-$0.15/1M tokens
Output price-$0.60/1M tokens
Providers-

Capabilities

CapabilityGemini 1.5 Pro 002Llama 4 Maverick 17B Instruct FP8
VisionNoYes
MultimodalNoYes
ReasoningNoNo
Function callingNoNo
Tool useNoNo
Structured outputsNoYes
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: Llama 4 Maverick 17B Instruct FP8, multimodal input: Llama 4 Maverick 17B Instruct FP8, and structured outputs: Llama 4 Maverick 17B Instruct FP8. 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: Gemini 1.5 Pro 002 has no token price sourced yet and Llama 4 Maverick 17B Instruct FP8 has $0.15/1M input tokens. Provider availability is 0 tracked routes versus 10. Treat unknown pricing as an integration gap, then verify the route you will actually call before estimating production spend.

Choose Gemini 1.5 Pro 002 when long-context analysis and larger context windows are central to the workload. Choose Llama 4 Maverick 17B Instruct FP8 when vision-heavy evaluation and broader provider choice 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.

FAQ

Which has a larger context window, Gemini 1.5 Pro 002 or Llama 4 Maverick 17B Instruct FP8?

Gemini 1.5 Pro 002 supports 2m tokens, while Llama 4 Maverick 17B Instruct FP8 supports 1m tokens. That gap matters most for long documents, large codebases, retrieval-heavy agents, and conversations where earlier context must remain visible.

Is Gemini 1.5 Pro 002 or Llama 4 Maverick 17B Instruct FP8 open source?

Gemini 1.5 Pro 002 is listed under Proprietary. Llama 4 Maverick 17B Instruct FP8 is listed under Llama 4 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, Gemini 1.5 Pro 002 or Llama 4 Maverick 17B Instruct FP8?

Llama 4 Maverick 17B Instruct FP8 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.

Which is better for multimodal input, Gemini 1.5 Pro 002 or Llama 4 Maverick 17B Instruct FP8?

Llama 4 Maverick 17B Instruct FP8 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 structured outputs, Gemini 1.5 Pro 002 or Llama 4 Maverick 17B Instruct FP8?

Llama 4 Maverick 17B Instruct FP8 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 Gemini 1.5 Pro 002 and Llama 4 Maverick 17B Instruct FP8?

Gemini 1.5 Pro 002 is available on the tracked providers still being sourced. Llama 4 Maverick 17B Instruct FP8 is available on Microsoft Foundry, Together AI, OpenRouter, Fireworks AI, and DeepInfra. 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.