LLM Pricing
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yi-large

fireworks_ai · chat model

yi-large is listed here as a chat model from fireworks_ai. 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
32.8K
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 benchmarks Review benchmark rows by family and benchmark label without cross-benchmark ranking. 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
32.8K
Max input tokens
32.8K
Max output tokens
32.8K
Max tokens
32.8K

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 —

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
yi-large
fireworks_ai
In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
text
Output: text
Response schema
32.8K
Current model
Reference row

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

Model Cost Input shape Features Context Why it is close
deepseek-r1
fireworks_ai
In $3.0000 / 1M tokens
Out $8.0000 / 1M tokens
text
Output: text
Response schema
20.5K
Same provider
Overall 88%
qwen2-72b-instruct
fireworks_ai
In $0.9000 / 1M tokens
Out $0.9000 / 1M tokens
text
Output: text
Response schema
32.8K
Same provider
Overall 86%
deepseek-r1-basic
fireworks_ai
In $0.5500 / 1M tokens
Out $2.1900 / 1M tokens
text
Output: text
Response schema
20.5K
Same provider
Overall 84%
deepseek-r1-0528
fireworks_ai
In $3.0000 / 1M tokens
Out $8.0000 / 1M tokens
text
Output: text
Response schema
160.0K
Same provider
Overall 81%
deepseek-coder-v2-instruct
fireworks_ai
In $1.2000 / 1M tokens
Out $1.2000 / 1M tokens
text
Output: text
Response schema
65.5K
Same provider
Overall 81%
llama-v3p1-405b-instruct
fireworks_ai
In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
text
Output: text
Response schema
16.4K
Same provider
Overall 76%
deepseek-v3
fireworks_ai
In $0.9000 / 1M tokens
Out $0.9000 / 1M tokens
text
Output: text
Response schema
8.2K
Same provider
Overall 75%
deepseek-v3-0324
fireworks_ai
In $0.9000 / 1M tokens
Out $0.9000 / 1M tokens
text
Output: text
Response schema
163.8K
Same provider
Overall 74%
meta.llama3-70b-instruct-v1:0
Bedrock
In $2.6500 / 1M tokens
Out $3.5000 / 1M tokens
text
Output: text
Low overlap
8.2K
Text covered
Overall 61%
meta.llama3-70b-instruct-v1:0
Bedrock
In $2.6500 / 1M tokens
Out $3.5000 / 1M tokens
text pdf
Output: text
Low overlap
2.0K
Text covered
Overall 58%
meta.llama3-70b-instruct-v1:0
Bedrock
In $2.6500 / 1M tokens
Out $3.5000 / 1M tokens
text pdf
Output: text
Low overlap
2.0K
Text covered
Overall 58%
mistral-nemo@2407
vertex_ai-mistral_models
In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
text
Output: unknown
Low overlap
128.0K
Partial I/O overlap
Overall 24%
Missing text
Qwen3-235B-A22B-Instruct-2507
crusoe
In $3.0000 / 1M tokens
Out $3.0000 / 1M tokens
text
Output: unknown
Low overlap
262.1K
Partial I/O overlap
Overall 22%
Missing text