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GPT-5.2 Pro vs Llama 3.1 Euryale 70B v2.2

Llama 3.1 Euryale 70B v2.2 costs 197.6x less per output token than GPT-5.2 Pro ($0.85 vs $168.00 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace GPT-5.2 Pro Replace Llama 3.1 Euryale 70B v2.2
GPT-5.2 ProOpenAI
Coding
No data
Overall
No data
Output $/M
$168.00
S Llama 3.1 Euryale 70B v2.2Sao10K
Coding
No data
Overall
No data
Output $/M
$0.85
vs $168.00 vs $0.85 per 1M output tokens. Llama 3.1 Euryale 70B v2.2 is 197.6x cheaper.

GPT-5.2 Pro or Llama 3.1 Euryale 70B v2.2: which to pick

Neither model has a coding score yet, so the two cannot be ranked on coding.

Pick GPT-5.2 Pro for a larger context window (400K against 131K tokens).

Model AGPT-5.2 ProOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BLlama 3.1 Euryale 70B v2.2Sao10KNot benchmarkedNo coding benchmarkNo cost per solved task

No benchmark has tested both yet. GPT-5.2 Pro has results on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2; Llama 3.1 Euryale 70B v2.2 has none yet. Compare them on price and context instead.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GPT-5.2 Pro not benchmarked, Llama 3.1 Euryale 70B v2.2 not benchmarked.
Widest category
None yet: no category has been tested on both models.
Widest single gap
None yet: no benchmark has tested both models.
Output price
GPT-5.2 Pro $168.00 against Llama 3.1 Euryale 70B v2.2 $0.85 per million output tokens, 197.6x apart.
Context window
GPT-5.2 Pro takes 400K tokens, Llama 3.1 Euryale 70B v2.2 131K.

Benchmark by benchmark

Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.

IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
Intelligence benchmarks for GPT-5.2 Pro and Llama 3.1 Euryale 70B v2.2
BenchmarkGPT-5.2 ProLlama 3.1 Euryale 70B v2.2Leader
Epoch Capabilities Index156.3Not measuredOnly GPT-5.2 Pro measured
Neither model has a result on the other 1 board here
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index4 boards measured
Reasoning benchmarks for GPT-5.2 Pro and Llama 3.1 Euryale 70B v2.2
BenchmarkGPT-5.2 ProLlama 3.1 Euryale 70B v2.2Leader
ARC-AGI90.5%Not measuredOnly GPT-5.2 Pro measured
ARC-AGI-254.2%Not measuredOnly GPT-5.2 Pro measured
SimpleBench57.4%Not measuredOnly GPT-5.2 Pro measured
Chess puzzles60.0%Not measuredOnly GPT-5.2 Pro measured
Neither model has a result on the other 19 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Math benchmarks for GPT-5.2 Pro and Llama 3.1 Euryale 70B v2.2
BenchmarkGPT-5.2 ProLlama 3.1 Euryale 70B v2.2Leader
FrontierMath, tiers 1 to 374.0%Not measuredOnly GPT-5.2 Pro measured
FrontierMath, tier 446.0%Not measuredOnly GPT-5.2 Pro measured
Neither model has a result on the other 12 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index2 boards measured
Knowledge benchmarks for GPT-5.2 Pro and Llama 3.1 Euryale 70B v2.2
BenchmarkGPT-5.2 ProLlama 3.1 Euryale 70B v2.2Leader
PRBench Finance46.3%Not measuredOnly GPT-5.2 Pro measured
PRBench Legal45.4%Not measuredOnly GPT-5.2 Pro measured
Neither model has a result on the other 18 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GPT-5.2 Pro$0.105Fits in one request
Llama 3.1 Euryale 70B v2.2$0.0013Fits in one request

Llama 3.1 Euryale 70B v2.2 costs less

Repository review

50K input + 3K output tokens

GPT-5.2 Pro$1.55Fits in one request
Llama 3.1 Euryale 70B v2.2$0.045Fits in one request

Llama 3.1 Euryale 70B v2.2 costs less

Agent loop

200K input + 10K output tokens

GPT-5.2 Pro$5.88Fits in one request
Llama 3.1 Euryale 70B v2.2$0.178Exceeds the context window

Llama 3.1 Euryale 70B v2.2 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GPT-5.2 Pro and Llama 3.1 Euryale 70B v2.2
SpecificationOpenAI GPT-5.2 ProSao10K Llama 3.1 Euryale 70B v2.2
MakerOpenAISao10K
WeightsNo public weights listedOpen weights
ReleasedDecember 10, 2025August 28, 2024
Context window400K131K
Input $/Mtok$21.00$0.85
Output $/Mtok$168.00$0.85
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.2 Pro better than Llama 3.1 Euryale 70B v2.2 for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Pick GPT-5.2 Pro for a larger context window (400K against 131K tokens).

Which is cheaper, GPT-5.2 Pro or Llama 3.1 Euryale 70B v2.2?

GPT-5.2 Pro costs $21.00 per million input tokens and $168.00 per million output tokens; Llama 3.1 Euryale 70B v2.2 costs $0.85 and $0.85. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-5.2 Pro or Llama 3.1 Euryale 70B v2.2?

GPT-5.2 Pro, with 400K tokens against 131K.

Has any benchmark tested both GPT-5.2 Pro and Llama 3.1 Euryale 70B v2.2?

No benchmark has tested both yet. GPT-5.2 Pro has results on Epoch Capabilities Index, ARC-AGI and ARC-AGI-2; Llama 3.1 Euryale 70B v2.2 has none yet. Compare them on price and context instead. Data as of October 22, 2026.

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