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GLM 5.3 FlashX vs Llama 3.1 Euryale 70B v2.2

Llama 3.1 Euryale 70B v2.2 costs 1.5x less per output token than GLM 5.3 FlashX ($0.85 vs $1.25 per million). Updated October 22, 2026; no benchmark has tested both models yet.

Replace GLM 5.3 FlashX Replace Llama 3.1 Euryale 70B v2.2
GLM 5.3 FlashXZ.ai
Coding
No data
Overall
No data
Output $/M
$1.25
S Llama 3.1 Euryale 70B v2.2Sao10K
Coding
No data
Overall
No data
Output $/M
$0.85
vs $1.25 vs $0.85 per 1M output tokens. Llama 3.1 Euryale 70B v2.2 is 1.5x cheaper.

GLM 5.3 FlashX 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 GLM 5.3 FlashX for a larger context window (1.05M against 131K tokens).

Model AGLM 5.3 FlashXZ.aiNot 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 either model yet, so price and context are the only way to compare them.

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
GLM 5.3 FlashX 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
GLM 5.3 FlashX $1.25 against Llama 3.1 Euryale 70B v2.2 $0.85 per million output tokens, 1.5x apart.
Context window
GLM 5.3 FlashX takes 1.05M 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.

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

GLM 5.3 FlashX$0.0010Fits in one request
Llama 3.1 Euryale 70B v2.2$0.0013Fits in one request

GLM 5.3 FlashX costs less

Repository review

50K input + 3K output tokens

GLM 5.3 FlashX$0.022Fits in one request
Llama 3.1 Euryale 70B v2.2$0.045Fits in one request

GLM 5.3 FlashX costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 FlashX$0.086Fits in one request
Llama 3.1 Euryale 70B v2.2$0.178Exceeds the context window

GLM 5.3 FlashX 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 GLM 5.3 FlashX and Llama 3.1 Euryale 70B v2.2
SpecificationZ.ai GLM 5.3 FlashXSao10K Llama 3.1 Euryale 70B v2.2
MakerZ.aiSao10K
WeightsNo public weights listedOpen weights
ReleasedSeptember 18, 2026August 28, 2024
Context window1.05M131K
Input $/Mtok$0.37$0.85
Output $/Mtok$1.25$0.85
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it00
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 FlashX 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 GLM 5.3 FlashX for a larger context window (1.05M against 131K tokens).

Which is cheaper, GLM 5.3 FlashX or Llama 3.1 Euryale 70B v2.2?

GLM 5.3 FlashX costs $0.37 per million input tokens and $1.25 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, GLM 5.3 FlashX or Llama 3.1 Euryale 70B v2.2?

GLM 5.3 FlashX, with 1.05M tokens against 131K.

Has any benchmark tested both GLM 5.3 FlashX and Llama 3.1 Euryale 70B v2.2?

No benchmark has tested either model yet, so price and context are the only way to compare them. Data as of October 22, 2026.

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