us.meta.llama4-scout-17b-instruct-v1:0
bedrock_converse · chat model
us.meta.llama4-scout-17b-instruct-v1:0 is listed here as a chat model from bedrock_converse. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.
Input
$0.1700 / 1M tokens
Output
$0.6600 / 1M tokens
Cached input
N/A
Context
4.1K
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 | $0.1700 / 1M tokens |
| Output | $0.6600 / 1M tokens |
| Embedding | $0.1700 / 1M tokens |
| Batch input | $0.0850 / 1M tokens |
| Batch output | $0.3300 / 1M tokens |
Token limits
Context window
4.1K
Max input tokens
128.0K
Max output tokens
4.1K
Max tokens
4.1K
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 |
Docs
| Official docs |
Similar models
This list is ranked by overall similarity. Use filters to emphasize the lens that matters most for the replacement you are making.
Comparing from
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| us.meta.llama4-scout-17b-instruct-v1:0 bedrock_converse | In $0.1700 / 1M tokens Out $0.6600 / 1M tokens | imagetext
Output: text | Function calling | 4.1K | Current model Reference row |
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| meta.llama4-scout-17b-instruct-v1:0 bedrock_converse | In $0.1700 / 1M tokens Out $0.6600 / 1M tokens | imagetext
Output: text | Function calling | 4.1K | Same provider Overall 100% |
| meta.llama4-maverick-17b-instruct-v1:0 bedrock_converse | In $0.2400 / 1M tokens Out $0.9700 / 1M tokens | imagetext
Output: text | Function calling | 4.1K | Same provider Overall 94% |
| us.meta.llama4-maverick-17b-instruct-v1:0 bedrock_converse | In $0.2400 / 1M tokens Out $0.9700 / 1M tokens | imagetext
Output: text | Function calling | 4.1K | Same provider Overall 94% |
| 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 | Same provider Overall 92% |
| 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 | Same provider Overall 80% Missing image |
| eu.meta.llama3-2-3b-instruct-v1:0 Bedrock | In $0.1900 / 1M tokens Out $0.1900 / 1M tokens | imagetext
Output: text | Function calling | 4.1K | Partial I/O overlap Overall 79% Missing image |
| eu.mistral.pixtral-large-2502-v1:0 bedrock_converse | In $2.0000 / 1M tokens Out $6.0000 / 1M tokens | imagetext
Output: image, text | Function calling | 4.1K | Same provider Overall 74% |
| magistral-small vercel_ai_gateway | In $0.5000 / 1M tokens Out $1.5000 / 1M tokens | imagetext
Output: text | Function calling | 64.0K | Text + image covered Overall 74% |
| gpt-4o-mini-2024-07-18 Azure | In $0.1650 / 1M tokens Out $0.6600 / 1M tokens | imagetext
Output: text | Function calling | 16.4K | Text + image covered Overall 68% |
| gpt-4o-mini Azure | In $0.1650 / 1M tokens Out $0.6600 / 1M tokens | imagetext
Output: text | Function calling | 16.4K | Text + image covered Overall 68% |
| gpt-4o-mini-2024-07-18 Azure | In $0.1650 / 1M tokens Out $0.6600 / 1M tokens | imagetext
Output: text | Function calling | 16.4K | Text + image covered Overall 68% |
| gpt-4o-mini-2024-07-18 Azure | In $0.1650 / 1M tokens Out $0.6600 / 1M tokens | imagetext
Output: text | Function calling | 16.4K | Text + image covered Overall 68% |
| grok-3-fast vercel_ai_gateway | In $5.0000 / 1M tokens Out $25.0000 / 1M tokens | imagetext
Output: text | Function calling | 131.1K | Text + image covered Overall 66% |
| Phi-3-medium-128k-instruct azure_ai | In $0.1700 / 1M tokens Out $0.6800 / 1M tokens | imagetext
Output: text | Low overlap | 4.1K | Partial I/O overlap Overall 63% Missing image |
No models match this filter.