meta.llama-4-maverick-17b-128e-instruct-fp8
oci · chat model
meta.llama-4-maverick-17b-128e-instruct-fp8 is listed here as a chat model from oci. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Quick read
Best for
Use this page when you need a fast view of cost, context size, and supported features before testing the model in your own workload.
Things to verify
Always check the provider page for discounts, cache pricing, region rules, and any model limits that may not appear in public metadata.
Pricing
| Item | Price |
|---|---|
| Input | $0.7200 / 1M tokens |
| Output | $0.7200 / 1M tokens |
| Embedding | $0.7200 / 1M tokens |
Token limits
Capabilities
| Capability | Supported |
|---|---|
| Vision | — |
| Function calling | ✅ |
| Parallel function calling | — |
| Tool choice | — |
| Prompt caching | — |
| Reasoning | — |
| Response schema | — |
| System messages | — |
| Audio input | — |
| Audio output | — |
| Web search | — |
| PDF input | — |
| Video input | — |
Benchmarks
Most benchmark rows are attached to the base model family rather than this provider route. Open benchmark explorer
| Benchmark | Score | Metric | Scope | Checked | Source |
|---|---|---|---|---|---|
| MMMU | 73.4 | accuracy | Base model: Llama 4 (Llama 4 Maverick) | 2026-05-31 | Link |
| ChartQA | 90.0 | relaxed_accuracy | Base model: Llama 4 (Llama 4 Maverick) | 2026-05-31 | Link |
| DocVQA | 94.4 | anls | Base model: Llama 4 (Llama 4 Maverick) | 2026-05-31 | Link |
| MMLU-Pro | 80.5 | macro_avg/acc | Base model: Llama 4 (Llama 4 Maverick) | 2026-05-31 | Link |
| GPQA Diamond | 69.8 | accuracy | Base model: Llama 4 (Llama 4 Maverick) | 2026-05-31 | Link |
| Artificial Analysis Intelligence Index | 18.4 | score | Base model: llama-4 (meta-llama/llama-4-maverick) | 2026-05-31 | Link |
| Artificial Analysis Coding Index | 15.6 | score | Base model: llama-4 (meta-llama/llama-4-maverick) | 2026-05-31 | Link |
| Artificial Analysis Agentic Index | 7.2 | score | Base model: llama-4 (meta-llama/llama-4-maverick) | 2026-05-31 | Link |
Sources
| Source links | |
| Pricing data | LiteLLM model cost map |
| Synced at | 2026-05-28 |
Similar models
This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| meta.llama-4-maverick-17b-128e-instruct-fp8 oci | In $0.7200 / 1M tokens Out $0.7200 / 1M tokens |
Output: unknown | Function calling | 4.0K | Current model Reference row |
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| meta.llama-3.3-70b-instruct oci | In $0.7200 / 1M tokens Out $0.7200 / 1M tokens |
Output: unknown | Function calling | 4.0K | Same provider Overall 60% |
| meta.llama-4-scout-17b-16e-instruct oci | In $0.7200 / 1M tokens Out $0.7200 / 1M tokens |
Output: unknown | Function calling | 4.0K | Same provider Overall 60% |
| meta.llama-3.1-70b-instruct oci | In $0.7200 / 1M tokens Out $0.7200 / 1M tokens |
Output: unknown | Function calling | 4.0K | Same provider Overall 60% |
| meta.llama-3.3-70b-instruct-fp8-dynamic oci | In $0.7200 / 1M tokens Out $0.7200 / 1M tokens |
Output: unknown | Function calling | 4.0K | Same provider Overall 60% |
| meta.llama3-3-70b-instruct-v1:0 bedrock_converse | In $0.7200 / 1M tokens Out $0.7200 / 1M tokens | text
Output: text | Function calling | 4.1K | Partial I/O overlap Overall 60% |
| us.meta.llama3-3-70b-instruct-v1:0 bedrock_converse | In $0.7200 / 1M tokens Out $0.7200 / 1M tokens | imagetext
Output: text | Function calling | 4.1K | Partial I/O overlap Overall 60% |
| cohere.command-latest oci | In $1.5600 / 1M tokens Out $1.5600 / 1M tokens |
Output: unknown | Function calling | 4.0K | Same provider Overall 49% |
| cohere.command-a-03-2025 oci | In $1.5600 / 1M tokens Out $1.5600 / 1M tokens |
Output: unknown | Function calling | 4.0K | Same provider Overall 49% |
| command-r-plus Azure | In $3.0000 / 1M tokens Out $15.0000 / 1M tokens | text
Output: text | Function calling | 4.1K | Partial I/O overlap Overall 42% |
| Mixtral-8x22B-Instruct-v0.1 anyscale | In $0.9000 / 1M tokens Out $0.9000 / 1M tokens |
Output: unknown | Function calling | 65.5K | Partial I/O overlap Overall 42% |
| Mistral-7B-Instruct-v0.1 anyscale | In $0.1500 / 1M tokens Out $0.1500 / 1M tokens |
Output: unknown | Function calling | 16.4K | Partial I/O overlap Overall 33% |
| Mixtral-8x7B-Instruct-v0.1 anyscale | In $0.1500 / 1M tokens Out $0.1500 / 1M tokens |
Output: unknown | Function calling | 16.4K | Partial I/O overlap Overall 33% |
| mistral-large-2402 Azure | In $8.0000 / 1M tokens Out $24.0000 / 1M tokens |
Output: unknown | Function calling | 32.0K | Partial I/O overlap Overall 28% |
| mistral-large-latest Azure | In $8.0000 / 1M tokens Out $24.0000 / 1M tokens |
Output: unknown | Function calling | 32.0K | Partial I/O overlap Overall 28% |
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