LLM Pricing
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mistral-nemo@2407

vertex_ai-mistral_models · chat model

mistral-nemo@2407 is listed here as a chat model from vertex_ai-mistral_models. This page shows simple API pricing, token limits, and capability flags so you can compare it with similar options.

Input
$3.0000 / 1M tokens
Output
$3.0000 / 1M tokens
Cached input
N/A
Context
128.0K
Compare similar models Open a side-by-side table using this route and the closest match from the current catalog. Estimate workload cost Use token counts, request volume, and cache assumptions to check a realistic monthly bill. Explore benchmark family Review source-backed benchmark rows for the attached base model family. Check data sources See how pricing data is generated and what still needs provider verification.

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
$3.0000 / 1M tokens
Output
$3.0000 / 1M tokens
Embedding
$3.0000 / 1M tokens

Token limits

Context window
128.0K
Max input tokens
128.0K
Max output tokens
128.0K
Max tokens
128.0K

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
Mistral Nemo 12B main benchmarks 83.5% HellaSwag (0-shot) Base model: Mistral Nemo (mistralai/Mistral-Nemo-Base-2407) 2026-05-31 Link
Mistral Nemo 12B main benchmarks 76.8% Winogrande (0-shot) Base model: Mistral Nemo (mistralai/Mistral-Nemo-Base-2407) 2026-05-31 Link
Mistral Nemo 12B main benchmarks 60.6% OpenBookQA (0-shot) Base model: Mistral Nemo (mistralai/Mistral-Nemo-Base-2407) 2026-05-31 Link
Mistral Nemo 12B main benchmarks 70.4% CommonSenseQA (0-shot) Base model: Mistral Nemo (mistralai/Mistral-Nemo-Base-2407) 2026-05-31 Link
Mistral Nemo 12B main benchmarks 50.3% TruthfulQA (0-shot) Base model: Mistral Nemo (mistralai/Mistral-Nemo-Base-2407) 2026-05-31 Link
Mistral Nemo 12B main benchmarks 68.0% MMLU (5-shot) Base model: Mistral Nemo (mistralai/Mistral-Nemo-Base-2407) 2026-05-31 Link
Mistral Nemo 12B main benchmarks 73.8% TriviaQA (5-shot) Base model: Mistral Nemo (mistralai/Mistral-Nemo-Base-2407) 2026-05-31 Link
Mistral Nemo 12B main benchmarks 31.2% NaturalQuestions (5-shot) Base model: Mistral Nemo (mistralai/Mistral-Nemo-Base-2407) 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.

Comparing from
Model Cost Input shape Features Context Why it is close
mistral-nemo@2407
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In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
Output: unknown
Function callingTool choice
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Current model
Reference row

Overall blends cost, modality overlap, capabilities, and context.

Model Cost Input shape Features Context Why it is close
moonshot-v1-128k
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In $2.0000 / 1M tokens
Out $5.0000 / 1M tokens
Output: unknown
Function callingTool choice
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Partial I/O overlap
Overall 52%
moonshot-v1-128k-0430
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In $2.0000 / 1M tokens
Out $5.0000 / 1M tokens
Output: unknown
Function callingTool choice
131.1K
Partial I/O overlap
Overall 52%
moonshot-v1-auto
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In $2.0000 / 1M tokens
Out $5.0000 / 1M tokens
Output: unknown
Function callingTool choice
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Partial I/O overlap
Overall 52%
grok-3
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In $3.0000 / 1M tokens
Out $15.0000 / 1M tokens
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Output: text
Function callingTool choice
131.1K
Partial I/O overlap
Overall 51%
grok-3-mini-fast
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In $0.6000 / 1M tokens
Out $4.0000 / 1M tokens
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Output: text
Function callingTool choice
131.1K
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glm-4.5
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In $0.6000 / 1M tokens
Out $2.2000 / 1M tokens
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Output: text
Function callingTool choice
131.1K
Partial I/O overlap
Overall 50%
mistral-small-2503
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In $1.0000 / 1M tokens
Out $3.0000 / 1M tokens
Output: unknown
Function callingTool choice
128.0K
Same provider
Overall 46%
codestral-2@001
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In $0.3000 / 1M tokens
Out $0.9000 / 1M tokens
Output: unknown
Function callingTool choice
128.0K
Same provider
Overall 44%
codestral-2
vertex_ai-mistral_models
In $0.3000 / 1M tokens
Out $0.9000 / 1M tokens
Output: unknown
Function callingTool choice
128.0K
Same provider
Overall 44%
codestral-2@001
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In $0.3000 / 1M tokens
Out $0.9000 / 1M tokens
Output: unknown
Function callingTool choice
128.0K
Same provider
Overall 44%
codestral-2
vertex_ai-mistral_models
In $0.3000 / 1M tokens
Out $0.9000 / 1M tokens
Output: unknown
Function callingTool choice
128.0K
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Overall 44%
DeepSeek-R1-Turbo
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In $1.0000 / 1M tokens
Out $3.0000 / 1M tokens
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Output: text
Function callingTool choice
41.0K
Partial I/O overlap
Overall 44%
DeepSeek-R1-0528-Turbo
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In $1.0000 / 1M tokens
Out $3.0000 / 1M tokens
text
Output: text
Function callingTool choice
32.8K
Partial I/O overlap
Overall 43%
moonshot-v1-32k
moonshot
In $1.0000 / 1M tokens
Out $3.0000 / 1M tokens
Output: unknown
Function callingTool choice
32.8K
Partial I/O overlap
Overall 43%
moonshot-v1-32k-0430
moonshot
In $1.0000 / 1M tokens
Out $3.0000 / 1M tokens
Output: unknown
Function callingTool choice
32.8K
Partial I/O overlap
Overall 43%
codestral-2501
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In $0.2000 / 1M tokens
Out $0.6000 / 1M tokens
Output: unknown
Function callingTool choice
128.0K
Same provider
Overall 43%
gpt-35-turbo-16k-0613
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In $3.0000 / 1M tokens
Out $4.0000 / 1M tokens
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Output: text
Function callingTool choice
4.1K
Partial I/O overlap
Overall 43%
mistral-small
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In $1.0000 / 1M tokens
Out $3.0000 / 1M tokens
text
Output: text
Function callingTool choice
8.2K
Partial I/O overlap
Overall 40%
Qwen3-235B-A22B-Instruct-2507
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In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
Output: unknown
Function callingTool choice
262.1K
Partial I/O overlap
Overall 40%
llama-v3p1-405b-instruct
fireworks_ai
In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
text
Output: text
Function callingTool choice
16.4K
Partial I/O overlap
Overall 39%
gpt-3.5-turbo
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In $0.5000 / 1M tokens
Out $1.5000 / 1M tokens
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Output: text
Function callingTool choice
4.1K
Partial I/O overlap
Overall 32%
gpt-35-turbo
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In $0.5000 / 1M tokens
Out $1.5000 / 1M tokens
text
Output: text
Function callingTool choice
4.1K
Partial I/O overlap
Overall 32%
Llama-3.3-70B-Instruct
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In $0.7100 / 1M tokens
Out $0.7100 / 1M tokens
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Output: text
Function callingTool choice
2.0K
Partial I/O overlap
Overall 30%
gpt-4
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In $30.0000 / 1M tokens
Out $60.0000 / 1M tokens
imagetext
Output: text
Function callingTool choice
4.1K
Partial I/O overlap
Overall 27%
gpt-4-0613
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In $30.0000 / 1M tokens
Out $60.0000 / 1M tokens
text
Output: text
Function callingTool choice
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Partial I/O overlap
Overall 27%
yi-large
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In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
text
Output: text
Low overlap
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Partial I/O overlap
Overall 24%
meta.llama3-70b-instruct-v1:0
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In $2.6500 / 1M tokens
Out $3.5000 / 1M tokens
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Low overlap
8.2K
Partial I/O overlap
Overall 18%
meta.llama3-70b-instruct-v1:0
Bedrock
In $2.6500 / 1M tokens
Out $3.5000 / 1M tokens
pdftext
Output: text
Low overlap
2.0K
Partial I/O overlap
Overall 18%
meta.llama3-70b-instruct-v1:0
Bedrock
In $2.6500 / 1M tokens
Out $3.5000 / 1M tokens
pdftext
Output: text
Low overlap
2.0K
Partial I/O overlap
Overall 18%