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Model comparison

GPT-5.3 Instant vs Llama 3 70B

Updated July 28, 2026. Public scores include evidence status and uncertainty. They are not guarantees for a specific workload.

GPT-5.3 Instant

OpenAI

—

Evidence status unavailable

90% interval unavailable

Llama 3 70B

Meta

—

Evidence status unavailable

90% interval unavailable

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. Use the documented cost, context, and runtime rows instead.

0 results are shared. Category rows based on different benchmark sets are marked directional and do not name a winner.

Which one for your work

Recommendations appear only when a shared evidence basis or an explicit operating constraint supports the call. Secondary and unsupported use cases stay disclosed below the initial list.

No workload recommendation clears the current evidence threshold.

Use the matched evidence, workload costs, and sourced specifications below instead of treating a point score as a universal answer.

Show secondary and unsupported calls

  • Coding work

    Code generation, repair, and software-engineering tasks

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Agentic work

    Tool use, computer use, and multi-step task completion

    Not enough matched evidence

    No shared weighted benchmark basis supports a winner.

    Confidence: limited

  • Long documents

    Prompts that approach the documented context limit

    No clear pick

    The documented context windows are equal.

    Confidence: documented

  • Chat turn cost

    1K fresh input + 500 output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

  • Cache-heavy agent loop cost

    200K cached + 20K fresh input + 10K output tokens

    Not enough matched evidence

    The page does not recommend a cost winner because at least one model cannot fit the stated workload in one request. GPT-5.3 Instant does not fit this workload in one request. Llama 3 70B does not fit this workload in one request. GPT-5.3 Instant has no published cached-input rate, so cached tokens use its listed input rate. Llama 3 70B has no comparable published API token rate.

    Confidence: rate-fallback

  • Repository review cost

    50K fresh input + 3K output tokens

    Not enough matched evidence

    A complete comparable API-rate estimate is not available for both models.

    Confidence: listed-rates

What is actually comparable

Shared results can support a head-to-head reading. Results present for only one model describe coverage, not superiority.

Evidence parity totals are not available.
Shared results
0
GPT-5.3 Instant only
0
Llama 3 70B only
0
Like-for-like categories
0 / 8

Category results, on a stated basis

Each row states whether both averages use the same weighted benchmark set. Directional and not-comparable rows remain visible, but they never receive a winner in this template.

Agentic

Not comparable
GPT-5.3 Instant
Not measured
Llama 3 70B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Coding

Not comparable
GPT-5.3 Instant
Not measured
Llama 3 70B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Reasoning

Not comparable
GPT-5.3 Instant
Not measured
Llama 3 70B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Knowledge

Not comparable
GPT-5.3 Instant
Not measured
Llama 3 70B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Math

Not comparable
GPT-5.3 Instant
Not measured
Llama 3 70B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multilingual

Not comparable
GPT-5.3 Instant
Not measured
Llama 3 70B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Multimodal

Not comparable
GPT-5.3 Instant
Not measured
Llama 3 70B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Instruction following

Not comparable
GPT-5.3 Instant
Not measured
Llama 3 70B
Not measured
Weighted basis
0 vs 0 rows
Reading
Not comparable

Shape of the matched evidence

Only shared public evidence is shown. Sparse evidence stays a ruled list rather than being closed into a radar shape.

A shared-evidence shape is not available.

BenchLM does not draw a radar or infer missing axes when the matched evidence is too sparse.

What each workload costs

Three fixed token mixes turn per-token rates into comparable decisions. Each scenario states context fit and whether cached input had to fall back to the published list-input rate.

Chat turn

1K fresh input + 500 output tokens

GPT-5.3 Instant
$0.00875
Fits in one request
Llama 3 70B
Self-hosted; infrastructure cost varies
Fits in one request

Llama 3 70B has no comparable published API token rate.

Repository review

50K fresh input + 3K output tokens

GPT-5.3 Instant
$0.1295
Fits in one request
Llama 3 70B
Self-hosted; infrastructure cost varies
Fits in one request

Llama 3 70B has no comparable published API token rate.

Cache-heavy agent loop

200K cached + 20K fresh input + 10K output tokens

GPT-5.3 Instant
$0.525
Does not fit in one request
Cached input priced at the published list-input rate
Llama 3 70B
Self-hosted; infrastructure cost varies
Does not fit in one request
Cached-input rate unavailable

GPT-5.3 Instant does not fit this workload in one request. Llama 3 70B does not fit this workload in one request. GPT-5.3 Instant has no published cached-input rate, so cached tokens use its listed input rate. Llama 3 70B has no comparable published API token rate.

Specification differences

Sourced differences are shown directly. Missing facts stay explicit instead of being inferred from a model name or family.

Cached-input rate

A missing cached-input rate falls back to the listed input rate only in the stated workload estimate.

GPT-5.3 Instant

Not published

Llama 3 70B

No comparable hosted API rate

Reasoning profile

GPT-5.3 Instant

Reasoning

Llama 3 70B

Non-Reasoning

Weight access

GPT-5.3 Instant

Proprietary

Llama 3 70B

Open Weight

License

GPT-5.3 Instant

Proprietary

Llama 3 70B

Open Weight

Release date

GPT-5.3 Instant

2026-03-03

Llama 3 70B

2024-04-18

If you already use one of these models
Deployment change
The models list different providers, so authentication, endpoint behavior, limits, and feature support may change.
Quality signal
The public evidence has no benchmark result shared by both models, so it does not support a quality verdict.
Workload cost
A complete comparable API-rate estimate is not available for both models.
Context tradeoff
Both models list 128K.

Run the same representative tasks against both endpoints before changing production traffic.

Frequently asked questions

Which is better, GPT-5.3 Instant or Llama 3 70B?

The public evidence has no benchmark result shared by both models, so it does not support a quality verdict. The page therefore keeps the decision tied to the specific documented workload.

Which is better for coding, GPT-5.3 Instant or Llama 3 70B?

The published evidence does not provide a shared weighted coding basis for both models, so BenchLM does not name a coding winner.

Which is better for agentic tasks, GPT-5.3 Instant or Llama 3 70B?

The published evidence does not provide a shared weighted agentic tasks basis for both models, so BenchLM does not name a agentic tasks winner.

Which costs less, GPT-5.3 Instant or Llama 3 70B?

Both models do not have comparable published API token rates, so this page does not name a universal price winner.

Which has the larger context window, GPT-5.3 Instant or Llama 3 70B?

Both models list the same context window, 128K.

Related comparisons

Compare API pricing Read the methodology Open the model selector

Last updated July 28, 2026

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