DeepSeek R1 Distill Llama 70B vs Ember-1
Ember-1 leads the LLM Stats Score 43.6 to 14.5. DeepSeek R1 Distill Llama 70B is 34.3x cheaper per token.
DeepSeek · Fireworks AI · Updated for 2026
Which is better?
Ember-1 leads the overall LLM Stats Score 43.6 to 14.5, ranking #45 overall.
On price, DeepSeek R1 Distill Llama 70B is roughly 34.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Ember-1 also accepts a larger context window (1,040,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek R1 Distill Llama 70B
- cost matters — it's about 34.3x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Ember-1
- overall performance matters — it scores 43.6 and ranks #45 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you process long inputs — it offers a 1,040,000 token context window
- you want the most recent training data — it shipped Sep 2026
At a glance
The differences that matter most.
Individual benchmarks
4 reported for DeepSeek R1 Distill Llama 70B · 4 for Ember-1
DeepSeek R1 Distill Llama 70B and Ember-1don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek R1 Distill Llama 70B ($0.10/1M tokens) is 30.0x cheaper than Ember-1 ($3.00/1M tokens).
For output processing, DeepSeek R1 Distill Llama 70B ($0.40/1M tokens) is 37.5x cheaper than Ember-1 ($15.00/1M tokens).
In conclusion, Ember-1 is more expensive than DeepSeek R1 Distill Llama 70B.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Ember-1 has 2709.4B more parameters than DeepSeek R1 Distill Llama 70B, making it 3837.7% larger.
Context Window
Maximum input and output token capacity
Ember-1 accepts 1,040,000 input tokens compared to DeepSeek R1 Distill Llama 70B's 128,000 tokens. Only DeepSeek R1 Distill Llama 70B specifies output context (128,000 tokens).
License
Usage and distribution terms
DeepSeek R1 Distill Llama 70B is licensed under MIT, while Ember-1 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek R1 Distill Llama 70B was released on 2025-01-20, while Ember-1 was released on 2026-09-23.
Ember-1 is 20 months newer than DeepSeek R1 Distill Llama 70B.
Jan 20, 2025
1.7 years ago
Sep 23, 2026
2 weeks ago
1.7yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek R1 Distill Llama 70B is available from DeepInfra. Ember-1 is available from Fireworks.
DeepSeek R1 Distill Llama 70B
Ember-1
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek R1 Distill Llama 70B and Ember-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek R1 Distill Llama 70B vs Ember-1.