mistral.mistral-large-3-675b-instruct
bedrock_converse · chat model
mistral.mistral-large-3-675b-instruct 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
$0.5000 / 1M tokens
Output
$1.5000 / 1M tokens
Cached input
N/A
Context
8.2K
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 | $0.5000 / 1M tokens |
| Output | $1.5000 / 1M tokens |
| Embedding | $0.5000 / 1M tokens |
Token limits
Context window
8.2K
Max input tokens
128.0K
Max output tokens
8.2K
Max tokens
8.2K
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 |
|---|---|---|---|---|---|
| MMLU | 85.5 | accuracy | Base model: mistral-large-3 (Mistral Large 3) | 2026-05-31 | Link |
| MMLU-Pro | 78.0 | accuracy | Base model: mistral-large-3 (Mistral Large 3) | 2026-05-31 | Link |
| GPQA Diamond | 43.9 | accuracy | Base model: mistral-large-3 (Mistral Large 3) | 2026-05-31 | Link |
| HumanEval | 92.0 | pass@1 | Base model: mistral-large-3 (Mistral Large 3) | 2026-05-31 | Link |
| MATH-500 | 93.6 | accuracy | Base model: mistral-large-3 (Mistral Large 3) | 2026-05-31 | Link |
| AIME 2024 | 53.3 | accuracy | Base model: mistral-large-3 (Mistral Large 3) | 2026-05-31 | Link |
| AIME 2025 | 40.0 | accuracy | Base model: mistral-large-3 (Mistral Large 3) | 2026-05-31 | Link |
| SimpleQA | 23.8 | accuracy | Base model: mistral-large-3 (Mistral Large 3) | 2026-05-31 | Link |
Sources
| Source links | |
| Pricing data | LiteLLM model cost map |
| Synced at | 2026-05-28 |
Docs
| Official docs |
Similar models
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Comparing from
| Model | Cost | Input shape | Features | Context | Why it is close |
|---|---|---|---|---|---|
| mistral.mistral-large-3-675b-instruct bedrock_converse | In $0.5000 / 1M tokens Out $1.5000 / 1M tokens | imagetext
Output: text | Function callingSystem messages | 8.2K | Current model Reference row |
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Output: text | Function callingSystem messages | 8.2K | Same provider Overall 87% |
| qwen.qwen3-vl-235b-a22b bedrock_converse | In $0.5300 / 1M tokens Out $2.6600 / 1M tokens | imagetext
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Output: text | Function callingSystem messages | 8.2K | Same provider Overall 84% |
| mistral.ministral-3-3b-instruct bedrock_converse | In $0.1000 / 1M tokens Out $0.1000 / 1M tokens | imagetext
Output: text | Function callingSystem messages | 8.2K | Same provider Overall 83% |
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