Verified November 2026

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Claude Fable 5.1 vs Llama 3.3 70B

A straight cost comparison of Claude Fable 5.1 (Anthropic) and Llama 3.3 70B (Meta (Llama)), per 1,000,000 tokens, verified November 2026.

$10Claude Fable 5.1 input / 1M
$0.88Llama 3.3 70B input / 1M
95%Blended price gap
Llama 3.3 70BCheaper blended

Rate-by-rate comparison

USD per 1M tokens · November 2026
MetricClaude Fable 5.1Llama 3.3 70BWinner
Input / 1M$10$0.88Llama 3.3 70B
Cached input / 1M$0.25$0.088Llama 3.3 70B
Cache write / 1M$12.50—Llama 3.3 70B
Output / 1M$50$0.88Llama 3.3 70B
Context window1,000,000128,000Claude Fable 5.1
Batch APIYesYesTie
Long-context tierNoneNone—

For per-token metrics, the lower number wins. For context window and batch support, the higher or broader option wins. A dash means the provider does not publish that rate: a missing cache-write fee means writes are not billed per token, while a missing cached-input rate means cache hits bill at the full input rate.

Blended cost: 1M input + 250K output

ModelBlended costDifference
Claude Fable 5.1$22.50+$21.40
Llama 3.3 70B$1.10Cheaper

Ten workloads, two bills

The same two models, priced across ten workloads that differ only in their input:output ratio. Nothing else changes — no retries, no system prompt, no middleware.

WorkloadClaude Fable 5.1Llama 3.3 70BWinner
Classification
100K reqs · 500 in / 10 out
$550$44.88Llama 3.3 70B
Data extraction
10K reqs · 2K in / 200 out
$300$19.36Llama 3.3 70B
Support chat
1K reqs · 4K in / 600 out
$70$4.05Llama 3.3 70B
Code review
2K reqs · 8K in / 1.5K out
$310$16.72Llama 3.3 70B
Summarisation
1K reqs · 20K in / 1K out
$250$18.48Llama 3.3 70B
Agent loop
5K reqs · 12K in / 2K out
$1,100$61.60Llama 3.3 70B
Translation
500 reqs · 15K in / 15K out
$450$13.20Llama 3.3 70B
Long-document QA
200 reqs · 120K in / 800 out
$248$21.26Llama 3.3 70B
Cached RAG
1K reqs · 50K in (45K cached) / 1K out
$112$9.28Llama 3.3 70B
Nightly batch
10K reqs · 10K in / 2K out
$1,000$52.80Llama 3.3 70B

Claude Fable 5.1 wins 0 of 10, Llama 3.3 70B wins 10 of 10. The winner is set by the token mix, not by the headline rate.

Where the two bills cross over

Llama 3.3 70B is cheaper on both sides of the mix: $0.88 vs $10 per million input tokens, and $0.88 vs $50 per million output. No input:output ratio reverses that, so on price alone the other model never becomes the better choice — it has to win on context, latency or output quality.

Cost at four scales

The same support-chat workload (4K input, 600 output per request) at four monthly volumes.

Requests / monthClaude Fable 5.1Llama 3.3 70BDifference
100$7$0.405Llama 3.3 70B cheaper by $6.60
1,000$70$4.05Llama 3.3 70B cheaper by $65.95
10,000$700$40.48Llama 3.3 70B cheaper by $660
100,000$7,000$405Llama 3.3 70B cheaper by $6,595

What caching does to each bill

Caching only helps the part of the prompt that repeats. This is the support-chat workload (1,000 requests, 4,000 input tokens each) with an increasing share of that prompt served from a warm cache, written once on the first request.

Cached share of the promptClaude Fable 5.1Llama 3.3 70BWinner
0%$70$4.05Llama 3.3 70B
50%$50.52$2.47Llama 3.3 70B
80%$38.84$1.52Llama 3.3 70B
95%$33$1.04Llama 3.3 70B

Both models publish a cached-read rate, so the discount is comparable: Claude Fable 5.1 reads cache at $0.25 per million, Llama 3.3 70B at $0.088.

Which one should you pick?

Claude Fable 5.1 wins on none of the ten workloads above, while Llama 3.3 70B wins on classification, data extraction, support chat, code review, summarisation, agent loop, translation, long-document qa, cached rag, nightly batch.

Beyond price, the two differ on input rate ($10 vs $0.88); output rate ($50 vs $0.88); cached-input rate ($0.25 vs $0.088); cache-write rate ($12.50 vs —); context window (1,000,000 vs 128,000).

Batch mode is available on Claude Fable 5.1 and Llama 3.3 70B, which halves the nightly job. Both publish cached-input discounts, so a stable system prompt is worth caching on either.

FAQ

Is Claude Fable 5.1 cheaper than Llama 3.3 70B?

On a blended 1M-input-plus-250K-output workload, Llama 3.3 70B is cheaper by 95% ($1.10 vs $22.50). The gap changes for cache-heavy prompts and for batch jobs, as the workload table shows.

Which handles longer prompts, Claude Fable 5.1 or Llama 3.3 70B?

Llama 3.3 70B has the larger context window (1,000,000 vs 128,000 tokens). Neither model publishes a long-context surcharge.

Do both models support prompt caching?

Claude Fable 5.1 bills cached reads at $0.25 per 1M; Llama 3.3 70B at $0.088.

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